Dynamic pricing of network-accessible resources for stateful applications

ABSTRACT

Methods and apparatus for dynamic pricing of cloud resources for stateful applications are disclosed. A system includes a resource manager and a plurality of execution platforms. The resource manager stores client-provided application packages in a repository, where each package includes an executable object and has an associated pricing constraint. The resource manager selects a particular execution platform on which to schedule execution of the executable object of a particular application package, based at least in part on a current pricing of execution units of the particular execution platform and the pricing constraint of the application package. In response to a price-based interruption event, a representation of a state of the application is saved, and the execution of the application on the particular execution platform is stopped.

BACKGROUND

Many companies and other organizations operate computer networks thatinterconnect numerous computing systems to support their operations,such as with the computing systems being co-located (e.g., as part of alocal network) or instead located in multiple distinct geographicallocations (e.g., connected via one or more private or publicintermediate networks). For example, data centers housing significantnumbers of interconnected computing systems have become commonplace,such as private data centers that are operated by and on behalf of asingle organization, and public data centers that are operated byentities as businesses to provide computing resources to customers. Somepublic data center operators provide network access, power, and secureinstallation facilities for hardware owned by various customers, whileother public data center operators provide “full service” facilitiesthat also include hardware resources made available for use by theircustomers. However, as the scale and scope of typical data centers hasincreased, the tasks of provisioning, administering, and managing thephysical computing resources have become increasingly complicated.

The advent of virtualization technologies for commodity hardware hasprovided benefits with respect to managing large-scale computingresources for many customers with diverse needs, allowing variouscomputing resources to be efficiently and securely shared by multiplecustomers. For example, virtualization technologies may allow a singlephysical computing machine to be shared among multiple users byproviding each user with one or more virtual machines hosted by thesingle physical computing machine, with each such virtual machine beinga software simulation acting as a distinct logical computing system thatprovides users with the illusion that they are the sole operators andadministrators of a given hardware computing resource, while alsoproviding application isolation and security among the various virtualmachines. Furthermore, some virtualization technologies are capable ofproviding virtual resources that span two or more physical resources,such as a single virtual machine with multiple virtual processors thatspans multiple distinct physical computing systems. As another example,virtualization technologies may allow data storage hardware to be sharedamong multiple users by providing each user with a virtualized datastore which may be distributed across multiple data storage devices,with each such virtualized data store acting as a distinct logical datastore that provides users with the illusion that they are the soleoperators and administrators of the data storage resource.

In many environments, operators of provider networks that implementdifferent types of virtualized computing, storage, and/or othernetwork-accessible functionality allow customers to reserve or purchaseaccess to resources in any of several different resource acquisitionmodes. For example, a customer may reserve a virtual compute resourceinstance for a relatively long duration, such as one year or threeyears, or a customer may purchase resources for shorter terms on anad-hoc basis as needed. For some types of resource reservations, atleast a portion of the price paid by the customer may fluctuate overtime in response to changing demand and supply of the resources withinthe provider network. The provider network operator may have to try toensure that a number of potentially competing demands are met, e.g.,that all guaranteed commitments to clients (such as long-termreservations that have already been paid for) are honored, that thedynamically-varying component of resource pricing does not get so highthat customer satisfaction suffers, that the provider's data centerinvestment is justified by a reasonable level of resource utilizationand revenue, and so on. In business environments where clients maychoose from among multiple providers for network-based computingoptions, provider network operators may wish to maintain high levels ofcustomer satisfaction and customer retention, e.g., by making resourceacquisition easy and economical, and by reducing the complexity ofclient resource budget management as much as possible.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system environment, according to at leastsome embodiments.

FIGS. 2 a and 2 b illustrate example resource instance classificationapproaches, according to at least some embodiments.

FIG. 3 illustrates an example of a set of sources from which data may beobtained by a pricing optimizer to generate recommendations, accordingto one embodiment.

FIG. 4 illustrates a portion of an example web-based interface that maybe used to display past usage and billing information to a client,according to some embodiments.

FIG. 5 illustrates a portion of an example web-based interface that maybe used by a client to specify optimization preferences, according tosome embodiments.

FIG. 6 illustrates a portion of an example web-based interface that maybe used to provide one or more instance recommendations, according tosome embodiments.

FIG. 7 illustrates a portion of an example web-based interface that maybe used to display projections of future resource usage, according tosome embodiments.

FIG. 8 is a flow diagram illustrating aspects of the functionality of apricing optimizer, according to at least some embodiments.

FIG. 9 is a flow diagram illustrating a subset of the functions of apricing optimizer related to the use of a client-side metrics agent,according to at least some embodiments.

FIG. 10 is a flow diagram illustrating aspects of the functionality of apricing optimizer that implements a programmatic interface allowingclients to indicate optimization preferences, according to at least someembodiments.

FIG. 11 is a flow diagram illustrating aspects of the functionality of apricing optimizer that implements a programmatic interface supportingthird-party interactions, according to at least some embodiments.

FIG. 12 illustrates example interactions that may occur between a clientand a resource manager, and between a pricing optimizer and the resourcemanager, to implement automated implementation of instancerecommendations, according to one embodiment.

FIG. 13 illustrates a portion of an example web-based interface that maybe used by a client to opt-in to a service providing automatedimplementation of recommendations, according to some embodiments.

FIG. 14 is a flow diagram illustrating aspects of the operation of aresource manager supporting automated implementation of recommendationsfor reserved instance operations, according to at least one embodiment.

FIG. 15 is a flow diagram illustrating aspects of the operation of aresource manager configured to provide a programmatic interface to allowclients to opt-in for automated implementation of recommendations from apricing optimizer, according to at least one embodiment.

FIG. 16 illustrates an embodiment in which a resource manager mayfulfill instance requests specifying any of a plurality of levels ofinterruptibility using a dynamically sized set ofenhanced-interruptibility available instances.

FIG. 17 illustrates a portion of an example web-based interface that maybe implemented for supporting multiple instance interruptibility levels,according to some embodiments.

FIG. 18 illustrates a portion of an example web-based interface that maybe implemented to support upgrades between instance interruptibilitylevels, according to some embodiments.

FIG. 19 is a flow diagram illustrating aspects of the operation of aresource manager configured to support multiple instanceinterruptibility levels, according to at least one embodiment.

FIG. 20 is a flow diagram illustrating aspects of the operation of aresource manager configured to support upgrades between interruptibilitylevels, according to at least one embodiment.

FIG. 21 is a flow diagram illustrating aspects of the operation of aresource manager configured to assign instances to an available instancepool and at least one enhanced-interruptibility sub-pool, according toat least one embodiment.

FIG. 22 is a flow diagram illustrating aspects of the operation of aresource manager configured to resize instance pools based at least onpart on usage trends for on-reserved instances and on-demand instances,according to at least one embodiment.

FIG. 23 illustrates a system in which a resource manager is configurableto determine a dynamically varying price per execution unit of excessresource capacity, and use the price to select client-providedapplications for execution, according to at least some embodiments.

FIG. 24 illustrates example contents of an application package that maybe submitted by a client to a resource manager, according to at leastsome embodiments.

FIG. 25 illustrates example interactions between a client and a resourcemanager configured to provide quotes for completing execution of anapplication, according to at least some embodiments.

FIG. 26 is a flow diagram illustrating aspects of the operation of aresource manager configured to schedule execution of client-providedapplications on execution platforms with dynamically changing pricingper unit of execution, according to at least some embodiments.

FIG. 27 is a flow diagram illustrating aspects of the operation of aresource manager configured to provide quotes for completing executionof an application, according to at least some embodiments.

FIG. 28 illustrates a portion of an example web-based interface that maybe implemented to allow clients to provide application specifications tobe used to schedule the client applications on execution platforms,according to some embodiments.

FIG. 29 is a block diagram illustrating an example computer system thatmay be used in some embodiments.

While embodiments are described herein by way of example for severalembodiments and illustrative drawings, those skilled in the art willrecognize that embodiments are not limited to the embodiments ordrawings described. It should be understood, that the drawings anddetailed description thereto are not intended to limit embodiments tothe particular form disclosed, but on the contrary, the intention is tocover all modifications, equivalents and alternatives falling within thespirit and scope as defined by the appended claims. The headings usedherein are for organizational purposes only and are not meant to be usedto limit the scope of the description or the claims. As used throughoutthis application, the word “may” is used in a permissive sense (i.e.,meaning having the potential to), rather than the mandatory sense (i.e.,meaning must). Similarly, the words “include,” “including,” and“includes” mean including, but not limited to.

DETAILED DESCRIPTION OF EMBODIMENTS

Various embodiments of methods and apparatus for managing dynamicpricing, reservation and allocation of network-accessible resources aredescribed. Networks set up by an entity such as a company or a publicsector organization to provide one or more services (such as varioustypes of cloud-based computing or storage) accessible via the Internetand/or other networks to a distributed set of clients may be termedprovider networks in this document. Such a provider network may includenumerous data centers hosting various resource pools, such ascollections of physical and/or virtualized computer servers, storagedevices, networking equipment and the like, needed to implement anddistribute the infrastructure and services offered by the provider. Theresources may in some embodiments be offered to clients in units called“instances,” such as virtual or physical compute instances or storageinstances. A virtual compute instance may, for example, comprise one ormore servers with a specified computational capacity (which may bespecified by indicating the type and number of CPUs, the main memorysize, and so on) and a specified software stack (e.g., a particularversion of an operating system, which may in turn run on top of ahypervisor). A number of different types of computing devices may beused singly or in combination to implement the resources of the providernetwork in different embodiments, including general purpose or specialpurpose computer servers, storage devices, network devices and the like.In some embodiments a client or user may be provided direct access to aresource instance, e.g., by giving a user an administrator login andpassword. In other embodiments the provider network operator may allowclients to specify execution requirements for specified clientapplications, and schedule execution of the applications on behalf ofthe client on execution platforms (such as application server instances,Java™ virtual machines (JVMs), general purpose or special-purposeoperating systems, platforms that support various interpreted orcompiled programming languages such as Ruby, Perl, Python, C, C++ andthe like, or high-performance computing platforms) suitable for theapplications, without for example requiring the client to access aninstance or an execution platform directly. A given execution platformmay utilize one or more resource instances in some implementations; inother implementations multiple execution platforms may be mapped to asingle resource instance.

Operators of such provider networks may in some instances implement aflexible set of resource reservation, control and access interfaces fortheir clients. For example, a resource manager of the provider networkmay implement a programmatic resource reservation interface (e.g., via aweb site or a set of web pages) that allows clients to learn about,select, purchase access to, and/or reserve resource instances. It isnoted that at least in some of the various embodiments discussed below,where an entity such as a resource manager or a pricing optimizer isdescribed as implementing one or more programmatic interfaces such as aweb page or an API, an interface manager subcomponent of that entity maybe responsible for the interface-related functionality. In manyembodiments equivalent interface-related functionality may beimplemented by a separate or standalone interface manager, external tothe resource manager and the pricing optimizer. Such an interface mayinclude capabilities to allow browsing of a resource catalog, providedetails and specifications of the different types or sizes of resourcessupported, the different reservation types or modes supported, pricingmodels, and so on. The provider network may support several differentpurchasing modes (which may also be referred to herein as reservationmodes) in one embodiment: for example, long-term reservations, on-demandresource allocation, or spot-price-based resource allocation. Using thelong-term reservation mode, a client may make a low, one-time, upfrontpayment for a resource instance, reserve it for a specified durationsuch as a one or three year term, and pay a low hourly rate for theinstance; the client would be assured of having the reserved instanceavailable for the term of the reservation. Using on-demand mode, aclient could pay for capacity by the hour (or some appropriate timeunit), without any long-term commitments or upfront payments. In thespot-price mode, a client could specify the maximum price per unit timethat it is willing to pay for a particular type of resource, and if theclient's maximum price exceeded a dynamic spot price determined at leastin part by supply and demand, that type of resource would be provided tothe client. In some embodiments, dynamically resizable pools of resourceinstances may be set aside for the different reservation types ormodes—e.g., long-term reserved instances may be allocated from one pool,on-demand instances from another, and so on. During periods when thesupply of the requested resource type exceeded the demand, the spotprice may become significantly lower than the price for on-demand mode.In some implementations, if the spot price increases beyond the maximumbid specified by a client, a resource allocation may beinterrupted—i.e., a resource instance that was previously allocated tothe client may be reclaimed by the resource manager and may be allocatedto some other client that is willing to pay a higher price. Otherpurchasing modes or combinations of modes may be implemented by theresource manager in some embodiments.

The resource needs and resource budgets of a given client may vary overtime, often in ways that may not be predictable very far in advance. Atthe same time, the pricing for various types of resources of theprovider network may also vary dynamically. The tasks of meetingbudgeting targets and/or making the most effective use of a givenresource budget may therefore become fairly complicated. In order tomake it easier for clients to address these goals, in some embodiments aprovider network operator may provide clients with access to a pricingoptimizer tool. In one such embodiment, a pricing optimizer (aspects ofwhose functionality may be exposed to clients via programmaticinterfaces such as web pages or a web site) may be operable to obtainresource usage records of a client from one or more usage data sources,and determine a recommended course of action for the client with respectto future resource instance reservations and/or acquisitions based onthe usage records and/or other pieces of information. For example, inmaking the recommendation, the pricing optimizer may take into accountdata about the client's resource usage during earlier time periods(e.g., during the last month or the last three months) as indicated bythe usage records, the pricing policies and/or current prices ofdifferent types of resources in the various resource pools, and one ormore optimization goals of the client. Several different types of clientoptimization goals may be taken into account in various embodiments,including for example client budget limits, and/or goals for a targetnumber of available resource instances that the client wishes toacquire. Using these various types of information, the pricing optimizermay determine a recommended number and/or types of resource instancesthat the client should access over some future term, and provide anotification of the recommendation to the client.

In some embodiments the provider network may be organized into aplurality of geographical regions, and each region may include one ormore availability zones. An availability zone (which may also bereferred to as an availability container herein) in turn may compriseone or more distinct locations or data centers, engineered in such a waythat the resources in a given availability zone are insulated fromfailures in other availability zones. That is, a failure in oneavailability zone may not be expected to result in a failure in anyother availability zone; thus, the availability profile of a resourceinstance is intended to be independent of the availability profile of aresource instance in a different availability zone. Clients may be ableto protect their applications from failures at a single location bylaunching multiple application instances in respective availabilityzones. At the same time, in some implementations, inexpensive and lowlatency network connectivity may be provided between resource instancesthat reside within the same geographical region (and networktransmissions between resources of the same availability zone may beeven faster). The pricing optimizer may in one embodiment also providerecommendations for the target availability zone or zones in which aclient's instances should be located. For example, the client's resourceusage records may include Internet Protocol (IP) address informationthat allows the pricing optimizer to determine the sources anddestinations of at least some of the client's network traffic, which maybe useful in identifying the appropriate availability zones.

Various types of usage data sources from which the pricing optimizerobtains usage data to develop its recommendations may be employed indifferent embodiments. In some embodiments, where for example a clientalready uses some set of resource instances of the provider network,provider-side metrics agents deployed at various entities (such asresource instances, network devices and the like) within the providernetwork may serve as usage data sources for the pricing optimizer. Thetypes of usage information collected for a given resource or instancemay include, for example, uptime (i.e., the amount of time a resourceinstance was active or booted up), CPU utilization, memory utilization,I/O rates, I/O device utilization, network traffic rates, network deviceutilization, the operating system in use, the hypervisor in use, variousdetails of the software stack in use such as application server type andversion, and so on, depending on the type of resource. In otherembodiments, at least a portion of the usage records may be collectedfrom client premises or client networks outside the provider network.For example, in one such embodiment, an entity of the provider networkmay allow prospective (or current) clients to download installableclient-side metrics agents, which may then be deployed to collect usagestatistics from various devices (such as servers, storage devices, ornetwork devices) within the client's networks. The collected usage datamay then be transmitted back for analysis by the pricing optimizer,which may then be able to generate recommendations for the types andnumber of resource instances the client should acquire, e.g., to allowthe client to utilize the provider network's resources instead of atleast some portion of the client-side equipment.

In some embodiments an interface manager (which, as noted earlier, maybe incorporated within the pricing optimizer and/or a resource manager,or may be external to both the pricing optimizer and resource manager)may implement a programmatic interface, which may for example be exposedas one or more web pages, allowing clients to indicate optimizationgoals that the pricing optimizer should use when developingrecommendations. Using such an interface, a client may in oneimplementation indicate a resource usage budget limit (e.g., theequivalent of “I can spend at most $10,000 for resource instances overthe period Jul. 1, 2012-Sep. 30, 2012”), and the pricing optimizer mayattempt to determine recommendations that meet the budget limit. Inanother scenario, a client may indicate an instance availability countgoal (e.g., the equivalent of “For my applications to run effectively Imust have at least 100 instances of performance rating X”) in someembodiments. In environments where different interruptibility settingsare supported, e.g., where access to some resource instances may berevoked based on threshold conditions being reached, the pricingoptimizer may also receive indications of the interruptibilitypreferences of a client, and use those preferences in making itsrecommendations. Various combinations of different types of clientoptimization goals may be used in different embodiments. In oneimplementation the recommendations may include performance capacityratings for some or all of the resource instances that the client isbeing advised to acquire.

In some embodiments a programmatic interface implemented for the clientmay allow the client to specify various “what-if” scenarios (such asanticipated or speculative resource usage metrics), and the pricingoptimizer may provide recommendations based on the what-if scenarios. Inone embodiment a client may be allowed to use a programmatic interfaceto opt-in to receive notifications if the pricing optimizer is able tofind a way for the client to save a specified amount (e.g., the clientmay in effect inform the pricing optimizer “Please notify me if you canfind a way for me to save $10,000 while continuing to run myapplications”), and the optimizer may notify the client accordingly ifthe desired savings can be implemented. In another embodimentprogrammatic interfaces (such as an application programming interface orAPI) may be implemented to allow third parties, such as network servicecompanies or other intermediaries, to utilize the functionality of thepricing optimizer—e.g., to provide usage data and/or pricing/budgetinggoals to the optimizer and receive corresponding recommendations. Thirdparties may use such facilities to help guide their own clients, and/orto build their own resource management interfaces to extend the corefunctions supported by the pricing optimizer. Various other types ofservices and functions may be provided by the pricing optimizer indifferent embodiments—e.g., the pricing optimizer may suggest instancedowngrades (e.g., informing a client that they may request a lesspowerful resource instance than the one they are currently paying for)based on the client's resource usage statistics, or suggest areservation resale (e.g., recommend to a client that a long-termreservation should be listed on a reservation resale marketplace), andso on. In one embodiment, the pricing optimizer may be used to providerecommendations for reservations or allocations of execution units (suchas CPU-minutes CPU-hours, floating point operations (FLOPs), and thelike) instead of, or in addition to, reservations or allocations ofentire resource instances.

According to one embodiment, a client may opt in to allow a resourcemanager to automatically implement one or more recommendations made bythe pricing optimizer—for example, instead of or in addition to beingnotified regarding the recommendations. In one such embodiment, theclient may specify a set of resources, such as a set of reservedinstances, for which the client has approved automatedrecommendation-based actions. (The set of resources may be empty tobegin with, i.e., in some cases the client may utilize the resourcemanager to obtain all of its resource instances.) Subsequent to anindication of the opt-in by the client for such automated actions, whenthe resource manager receives a relevant recommendation generated by thepricing optimizer, at least a portion of the recommendation may be putinto effect, e.g., without the client having to take any additionalaction. For example, if the recommendation suggests that a particularresource reservation (e.g., a slot for a reserved instance) held by theclient should be listed for resale on a reservations resellingmarketplace, the resource manager may list the resource instance orreservation on the marketplace. If and when the listed resource instanceis resold (e.g., when a different client reserves the listed instance),the instance may be removed from the marketplace listing and/or from theset of resources reserved for the client. In some cases, other eventsmay cause a change in the status of the listed resource instance: e.g.,if the instance has been listed for a while and has not yet been resold,or if the pricing optimizer generates a new recommendation suggestingthat it is advisable to delist the instance from the marketplace (basedon pricing changes or increased resource demand from the client). If therecommendation generated by the pricing optimizer suggests that it isadvisable to procure another instance for the client (e.g., either as acheaper substitute for a reservation that is being resold, or simplybecause the client's resource demand is growing), the resource managermay identify an appropriate instance and reserve it or allocate it forthe client's use. The newly reserved or procured instance may beselected from an availability zone or region suggested in therecommendation.

The resource manager responsible for automating reservationmodifications and/or other actions in accordance with recommendationsgenerated by the pricing optimizer may be responsible for several otherrelated functions in some embodiments. For example, the resource managermay implement one or more programmatic interfaces (such as web pages,APIs or command-line interfaces) allowing clients to opt-in for theautomated implementation of the optimizer's recommendations, as well asone or more of the programmatic interfaces similar to those describedabove implementing aspects of the pricing optimizer functionality. Aprogrammatic interface allowing clients to specify budget constraints,availability zone preferences, and the like, to be used by the pricingoptimizer in generating recommendations may be implemented by theresource manager in one embodiment. In some implementations the resourcemanager may provide an interface that allows a client to specify aschedule for automated reservation optimization attempts—e.g., theclient may indicate that recommendations should be generated and/orimplemented on its behalf only during a timing window between midnightand 6 am, or at, most once a week or once a month. The client may alsoindicate a scheduling preference that allows the resource manager andthe pricing optimizer to control when recommendations are generatedand/or implemented in some implementations; i.e., a schedulingpreference that provides full flexibility for the timing ofrecommendation generation and implementation. In some embodiments, thefull flexibility option may represent the default behavior of thesystem, such that restrictions on the timing of the actions of theoptimizer and the resource manager may only be imposed in response tospecific demands from the client. Scheduling preferences may becommunicated to the pricing optimizer by the resource manager, and therecommendations may be generated in accordance with the preferences.

As noted above, in some embodiments resource instances and/or instancepools may have associated interruptibility settings—e.g., indicatingwhether an ongoing reservation or allocation period can be terminatedbefore the client that currently owns the reservation releases theinstance or completes the tasks for which the reservation or allocationwas made. In one such embodiment, each resource instance may have aninterruptibility property modifiable by the resource manager, and theresource manager may be responsible for modifying the interruptibilityproperties of various instances and determining appropriate prices forthe different supported interruptibility settings in accordance withsupply and demand. In one scenario, a set of currently idle resourceinstances may be assigned to an “available pool” of instances. Withinthe available pool, a subset of the instances may at a given time beconfigured as fully-interruptible instances, while the remaininginstances of the available pool may be configured to have any of one ormore enhanced interruptibility settings. That is, one or more sub-poolsof the available pool may be maintained to cater to requests forinstances with enhanced interruptibility requirements. The resourcemanager may allocate a fully-interruptible instance to a client, e.g.,based on a bid provided by the client in an instance acquisitionrequest, on the condition that the client's access to thefully-interruptible instance may be revoked by the resource manager atany point without notifying the client. However, the interruptibilitysetting of the instance may be upgraded in some embodiments, e.g., inresponse to an interruptibility upgrade request from the client. Forexample, the set of applications being run on the instance may haveseveral phases with different interruptibility needs. During some phasesit may be acceptable to run the application for a low price whilerunning the risk of being interrupted or stopped, while in other phasesthe client may be willing to pay a higher price in return for enhancedinterruptibility settings. In one embodiment, the interruptibilitysetting of a currently fully interruptible instance may be enhanced tonon-interruptible by the resource manager in response to an upgraderequest; e.g., the client may be given the ability to retain theinstance for a specified time, or until the client relinquishes access.

In another embodiment, the resource manager may implement one or morevariants of interruptibility settings that fall between thefully-interruptible setting and the non-interruptible setting. Forexample, the resource manager may allow a client to retain access to aresource instance for a delay interval (e.g., five minutes) after theclient receives an access revocation notification from the resourcemanager. A client may, in such an embodiment, request that theinterruptibility setting of one or more instances be modified tointerruptible-with-notification from fully-interruptible. The resourcemanager may accept (or deny) the request based on factors such as thecurrent supply of fully-interruptible or enhanced-interruptibilityinstances, the price the client is willing to pay for the upgrade, theprojected number of instance reservation requests, the projected rate ofrequests for on-demand instances, and so on. In some embodiments theresource manager may expose the different interruptibility settingssupported, and the current pricing for different interruptibilitylevels, to potential clients, and allow the clients to specify desiredinterruptibility settings in their instance acquisition requests.

The number of resource instances assigned to the available pool and itsenhanced-interruptibility sub-pool(s) may vary over time in someembodiments. Similarly, the prices associated with the differentinterruptibility settings may vary dynamically as well, based on supplyand demand. The billing amounts charged to a given client for use of agiven instance may be a function of the various interruptibilitysettings for the instance during the time that the instance wasallocated to the client, and the respective durations for which each ofthe interruptibility settings applied during the allocation period. Thecurrent price for a given interruptibility setting may be governed inpart by the current supply of instances with that interruptibilitysetting. In one implementation, for example, the current price of afully-interruptible instance may be dependent on the size of theavailable pool, while the current price for an enhanced-interruptibilityinstance may be dependent on the current size of theenhanced-interruptibility pool. Instances may be moved in and out of thevarious pools and sub-pools, and the corresponding prices may beadjusted dynamically, based on a number of different factors such ascurrent and anticipated demand (e.g., based on an analysis of usagetrends for reserved instances, on-demand instances, and/or upgraderequests), the price clients are willing to bid for fully-interruptibleinstances and enhanced-interruptibility instances, the number ofoutstanding unfulfilled reservation slots (i.e., the number of instancesthat have been reserved but are currently not activated by theirreservers), and so on. Interruptibility settings may be downgraded inresponse to client requests in some embodiments.

The resource manager may revoke access to an interruptible instance(with or without a revocation notification to the client currentlyaccessing the instance, and with or without a delay notification,depending on the interruptibility setting) for a variety of reasons. Forexample, access may be revoked if a fulfillment request for an existingreservation is received from another client, or if a higher bid for thesame type of instance is received from a different client. Instances maybe added to the available pool or one of the enhanced-interruptibilitysub-pools for a number of reasons as well—e.g., if a client holding areservation decides to resell the reservation, or if a reservationexpires, or if the demand for on-demand instances falls. In someembodiments where interruptions with notifications indicating delayintervals are supported, the delay interval for a given resourceinstance may itself be variable based on the amount the client iswilling to bid—e.g., for a higher bid, a longer delay may be allowedthan the delay for a lower bid. In another implementation the delay mayvary with the currently advertised price for enhanced-interruptibilityinstances—e.g., if demand for interruptible-with-notification instancesfalls, the delay period may be allowed to increase while keeping theprice fixed, or the price may be allowed to fall while keeping the delayfixed.

In some embodiments, excess compute and/or storage capacity may be soldat granularities other than entire resource instances. For example, tosupport a marketplace for spare computation cycles (in contrast to spareresource instances), in one embodiment clients may be allowed to provideexecutable applications to the resource manager, and the resourcemanager may schedule the applications on various execution platforms,such as JVMs or application server instances, without for examplenecessarily allocating entire resource instances to clients, orrequiring the clients to control or operate resource instances directly.The executable platforms may be mapped to resource instances in variousways in some such embodiments—e.g., one or more execution platforms maybe instantiated on a single resource instance, or a single executionplatform may run on portions or all of multiple resource instances.Prices for allocation, reservation, and use of the execution platformsmay vary dynamically based on supply and demand. In one embodiment ofsuch a system comprising a plurality of execution platforms, a resourcemanager may store a collection of one or more client-providedapplication packages, e.g., in an application repository, wherein eachapplication package includes an executable object of an application andhas an associated pricing constraint to be used to schedule execution ofthe executable object. The resource manager may select a particularexecution platform on which to schedule the execution of the executableobject of a particular application package based at least in part on acurrent price associated with the execution platform. If a price-basedinterruption event occurs, such as the arrival of a higher bid or a moreattractive pricing constraint for the type of execution platform beingused, the resource manager may save a representation of a state of theapplication, and stop the execution of the executable object. Theexecution of an application may also be stopped on a particular platformfor other reasons, such as an additional platform becoming available(potentially for a lower price).

Various types of pricing constraints may be specified for theapplications in different embodiments supporting execution platforms.For example, for execution platforms where the CPUs are expected to bekey determinants of application performance, clients may specify bidsfor execution units such as CPU-seconds, CPU-minutes, CPU-hours,floating point operations (FLOPs), integer operations, or CPU cycles(for one or more different CPU types supported by the resource manager).For other types of execution platforms and/or other types ofapplications, which may be disk I/O intensive or network intensive,execution units may include such metrics as total gigabytes of dataread/written to a storage device, total number of I/O operationsperformed, or total gigabytes of data transferred over a network. Bidsand/or prices may be expressible for combinations of units in someembodiments, e.g., CPU-seconds with a disk I/O transfer limit. In oneembodiment, a client may submit an application package to the resourcemanager and ask for a quote to complete the execution of theapplication. The resource manager may in such a case analyze theapplication package, the current and expected availability ofappropriate execution platforms and corresponding prices, and respondwith a quote for the application. The client may then respond to thequote with a bid, which the resource manager may accept or reject. Insome embodiments the resource manager may be capable of providing quotesfor completing the remainder of the execution of an application that hasalready been executing for a while. An application whose execution hasbeen stopped or suspended as a result of a price-based interruptionevent may be rescheduled for further execution, either at a differentexecution platform or the same execution platform that was usedpreviously, as the prices and/or availability of execution platformschange. In environments where different execution platforms run ondifferent hardware and software stacks, the current price of executingan application on a given execution platform may vary based on theperformance capabilities of the underlying hardware and/or software. Insome embodiments a resource manager may be capable of schedulingindividual threads of a multi-threaded or parallelized application ondifferent execution platforms.

The intelligence of the pricing optimizer may be utilized by theresource manager to support several of the functions described above insome embodiments. For example, the pricing optimizer may be helpful inanalyzing resource usage trends and deciding when and how to resize thedifferent instance pools (e.g., the available pool and theenhanced-interruptibility sub-pools). Similarly, the pricing optimizermay be used to select the most appropriate execution platform for aparticular application package, to decide how many available resourceinstances should be used for execution platforms (as opposed to beingused for enhanced-interruptibility sub-pools, for example). Pricingcomputations may also be performed with the optimizer's help in someimplementations. Further details of the operations of the pricingoptimizer and the resource manager in various embodiments are providedbelow in conjunction with the descriptions of FIGS. 1-29.

Example System Environment

FIG. 1 illustrates an example system environment, according to at leastsome embodiments. The system 100 includes a provider network 110comprising a plurality of resource instances 130, such as instances130A, 130B, 130D, 130E, 130G and 130H in one availability zone 120A, andinstances 130J, 130K, 130M, 130N, 130P, 130Q in a different availabilityzone 120B. The various resource instances 130 in the differentavailability zones 120 may be reserved and/or allocated for use byclients (or potential clients) such as client 148A and 148B. In theillustrated embodiment, system 100 includes a resource manager 180, apricing optimizer 181, and an interface manager 182. As noted earlier,in some embodiments the functionality of the interface manager 182 maybe implemented by a subcomponent of the resource manager 180 and/or asubcomponent of the pricing optimizer 181. The interface manager 182 mayin some embodiments implement one or more programmatic interfacesallowing clients 148 to search for, browse, reserve and acquireinstances 130 to obtain various types of services, e.g., to run and/oraccess various applications. In the illustrated embodiment, at a givenpoint in time, some or all of the instances 130 may be assigned toinstance pools (based in part on instance categorization approachessimilar to those illustrated in FIGS. 2 a and 2 b), such as reservedinstance pools 121A or 121B, on-demand instance pools 123A or 123B,available instance pool 125, or other pools such as 127. In someembodiments a given pool such as the available pool 125 may itselfcontain its own sub-pools, e.g., based on the modes of instancereservation and allocation supported. Each pool (or sub-pool) may havean associated pricing policy for its instances, as well as otherproperties such as interruptibility settings for the instances thathappen to be assigned to the pool or sub-pool. Additional detailsregarding the organization of the different types of pools, variouspricing policies and interruptibility policies supported in differentembodiments, and the logic that may be used to move instances from onepool or sub-pool to another, will be provided below. It is noted thatthe pools may represent logical collections or aggregations, so that,for example, the presence of two instances in the same pool or sub-poolmay not necessarily imply anything about the physical location of thehardware used for the two instances. Although the instances 130illustrated in FIG. 1 are shown as belonging to availability zones 120,in other embodiments the provider network 110 may be organizeddifferently: e.g., in some embodiments availability zones may not beimplemented. Availability zones 120 may be grouped into geographicregions (not shown in FIG. 1) in some embodiments. Instance pools may beimplemented within availability zones in some implementations (e.g.,each availability zone may have its own reserved instance pool), whilein other implementations an instance pool or sub-pool may span multipleavailability zones.

The pricing optimizer 181, which may exist as a separate entity in someembodiments and may be incorporated as an element of the resourcemanager 180 in other embodiments, may be configurable to obtaininformation from a variety of data sources to generate recommendationson the instances that a client 148 should acquire or reserve. Forexample, in the embodiment illustrated in FIG. 1, the pricing optimizer181 may obtain resource usage records or statistics from one or moreprovider-side metrics agents, such as agents 140A and 140B, which mayprovide information regarding the usage of various types of instances130 by a client 148 over some selected period of time. The pricingoptimizer 181 may use its knowledge of the trends of past or currentresource usage by a given client 148 to make projections about futureusage of different types of resources by the client 148. In someembodiments, resource usage metrics may also or instead be obtained fromclient-side devices external to the provider network 110. For example,in one implementation the pricing optimizer 181 or the resource manager180 may provide a downloadable or otherwise installable client-sidemetrics agent such as 190A to a client such as 148A, and the client 148Amay install and activate the agent or agents in the client's data centeror client-managed premises. The client-side metrics agent 190 may gatherresource usage information from various client devices 160 (e.g., 160Aand 160B in client network 150A of client 148A, or 160D and 160E inclient network 150B of client 148B), and transmit the usage informationto the pricing optimizer 181. The pricing optimizer 181 may use theclient-side usage metrics to help generate recommendations for the kindsof instances 130 that the client should consider for use. In some cases,the pricing optimizer 181 may obtain usage records from bothprovider-side metrics agents 140 and client-side metrics agents 190.

In addition to usage records, pricing optimizer 181 may also use anumber of other pieces of information to make its recommendations insome embodiments. For example, in one embodiment the interface managersubcomponents of pricing optimizer 181 (and/or the resource manager 180)may implement one or more programmatic interfaces, examples of whichwill be shown below, to allow clients 148 to specify one or morepreferences and/or optimization goals to serve as additional input forthe process of determining recommendations. In addition, therecommendations made by the pricing optimizer 181 may be dependent onvarious types of pricing information in some embodiments—for example,past pricing trends for different types and sizes of resource instances,pricing constraints specified by clients 148, anticipated future pricingtrends extrapolated or estimated by the pricing optimizer, and so on.Some or all of the types of information used by the pricing optimizer181 to make its recommendations, and the types of information maintainedby the resource manager for resource reservations, allocations andpricing, may be stored in a persistent store such as a resourcemanagement database 191 in some embodiments.

Resource Instances Categories and Associated Pricing Models

The resource instances 130 of a provider network may be grouped intoclasses or categories based on several different dimensions in someembodiments, and the pricing policies associated with different classesmay differ. FIGS. 2 a and 2 b illustrate example resource instanceclassification approaches, according to at least some embodiments. FIG.2 a illustrates an approach in which instances are classified based inpart on the timing or duration of instance allocations—i.e., on wheninstances are obtained by clients and when they are released by theclients. Three high-level types 201 of resource instances are shown:reserved instances 203, on-demand instances 205, and spot-instances 207,each with respective pricing policies 203P, 205P and 207P. In oneembodiment, a client 148 may reserve an instance for fairly longperiods, such as a one-year term or a three-year term in accordance withthe pricing policy 203P, by paying a low, one-time, upfront payment forthe instance, and then paying a low hourly rate for actual use of theinstance at any desired times during the term of the reservation. Thus,the client 148 may, by making the long-term reservation, be assured thatits reserved instance 203 will be available whenever it is needed.

If a client 148 does not wish to make a long-term reservation, theclient may instead opt to use on-demand instances 205 (or spot instances207). The pricing policy 205P for on-demand instances 205 may allow theclient 148 to pay for resource capacity by the hour with no long-termcommitment or upfront payments. The client 148 may decrease or increasethe resource capacity used, based on application needs, and may onlyhave to pay the hourly rate for the instances used. In some cases theper-hour pricing for on-demand instances may be higher than the hourlyrate for reserved instances, because the relatively long durations ofreservations may provides a more stable revenue stream to the operatorof the provider network than the potentially more dynamic revenue streamprovided by on-demand instances. Spot instances 207 may provide a thirdtype of resource purchasing and allocation model. The spot pricingpolicy 307P may allow a client 148 to specify the maximum hourly pricethat the client is willing to pay, and the resource manager 180 may seta spot price for a given set of resource instances 130 dynamically basedon the prices clients are willing to pay and on the number of instancesavailable to support the spot model. If a client 148's bid meets orexceeds the current spot price, an instance may be allocated to theclient. If the spot price rises beyond the bid of the client using aspot instance 207, access to the instance by the client may be revoked(e.g., the instance may be shut down).

The prices of reserved instances 203, on-demand instances 205, and spotinstances 207 may also vary based on the availability zones 120 orgeographic regions in which the instances are located. The operator ofprovider network 110 may have had to pay different costs for setting updata centers in different physical locations, and may have to payvarying location-dependent ongoing costs for infrastructure andmaintenance services such as network connectivity, cooling and so on,which may result in different pricing policies for differentavailability zones and/or regions. Fluctuations in supply and demand mayalso result in time-varying prices for the different types of instances.Of course, the price for a given long-term reservation may typicallyremain unchanged once a client completes the reservation.

In some embodiments, reserved instances 203 may be further classifiedbased on expected uptime ratios. The uptime ratio of a particularreserved instance 130 may be defined as the ratio of the amount of timethe instance is activated, to the total amount of time for which theinstance is reserved. Uptime ratios may also be referred to asutilizations in some implementations. If a client 148 expects to use areserved instance for a relatively small fraction of the time for whichthe instance is reserved (e.g., 30%-35% of a year-long reservation), theclient may decide to reserve the instance as a Low Uptime Ratio instance215, and pay a discounted hourly usage fee in accordance with theassociated pricing policy 215P. If the client 148 expects to have asteady-state workload that requires an instance to be up most of thetime, the client may reserve a High Uptime Ratio instance 211 andpotentially pay an even lower hourly usage fee, although in someembodiments the hourly fee may be charged for the entire duration of thereservation, regardless of the actual number of hours of use, inaccordance with pricing policy 211P. An option for Medium Uptime Ratioinstances 213, with a corresponding pricing policy 213P, may besupported in some embodiments as well, where the upfront costs and theper-hour costs fall between the corresponding High Uptime Ratio and LowUptime Ratio costs.

Instance pricing may also vary based on other factors. For example, inthe case of compute instances, the performance capacities of differentCPUs and other components of compute servers such as memory size maycome into play. FIG. 2 b shows an example classification of computeinstances based on instance performance ratings 251. Large instances 253may have more computing capacity than medium instances 255, which inturn may have more computing capacity than small instances 257.Accordingly, different pricing policies 253P, 255P and 257P may beimplemented for the different sizes of instances. In some embodiments,software features such as operating systems, hypervisors, middlewarestacks and the like may also be taken into account in determining thepricing policies associated with various instances. For both computeinstances and storage instances, storage device characteristics such astotal storage capacity, supported I/O rates and the like may be used todevelop pricing policies in some implementations. Pricing policies mayalso be determined by networking capabilities and networking usage(e.g., number of megabytes of data transferred, and/or the distancesover which network traffic is transmitted). Other classificationdimensions and techniques, including extensions of the basic hierarchiesshown in FIGS. 2 a and 2 b, may be implemented in other embodiments. Thevarious pricing policies, including static and dynamic components ofpricing, as well as location-dependent and location-independentcomponents, may be used by pricing optimizer 181 to make itsrecommendations, as described below in further detail. Some or all ofthe pricing information may be stored in resource management database191, and the pricing optimizer 181 may retrieve the information from thedatabase as needed. In some embodiments the resource instances of aprovider network may be organized as pools based on, for example, whichinstances are currently being used as on-demand instances (e.g., pools123A and 123B of FIG. 1), which instances are reserved (e.g., pools 121Aand 121B), which are currently idle or available (e.g., pool 125A), andso on.

Pricing Optimizer Information Sources

FIG. 3 illustrates an example of a set of sources from which data may begathered by pricing optimizer 181 to generate recommendations, accordingto one embodiment. As shown, the pricing optimizer may obtain clientoptimization goals and/or preferences 301, a variety of instance pricingdata 303 for different types of resource instances, provider-sideresource usage metrics 305, and/or client-side resource usage metrics307, and use any appropriate combination of these input sources todetermine instance recommendations 351 for a client 148.

In some embodiments, the pricing optimizer 181 and/or the resourcemanager 180 may implement one or more programmatic interfaces allowingclients to specify their optimization goals or preferences. For example,one or more web pages may be provided, using which clients 148 may enteror select their preferences for overall optimization goals (e.g., thelogical equivalent of “Give me any suggestions you have for reducing mybills”) and/or indicate more specific preferences (such as theequivalent of “I prefer to use large instances as often as possible” or“I prefer to use instances in availability zones X and Y if possible”).In some embodiments if a client 148 does not indicate a specificoptimization goal but does indicate that it is willing to getrecommendations, the pricing optimizer may use default optimizationgoals such as the logical equivalent of “Based on trends derived fromlast quarter's resource usage, identify the most economical instancetypes and quantities to use for the next quarter”. Clients 148 mayindicate preferences for any combination of various types of instancecharacteristics such as instance size, reserved vs. on-demand vs. spot,interruptibility settings, availability zones, operating systems,software stacks, and so on in some embodiments. In some embodiments theclient 148 may specify budget details—e.g., “I have a resource instancebudget limit of $50,000 for the period Jan. 1-Mar. 31, 2012” and requestthat the budget limits be used in generating the recommendations. In oneembodiment a client 148 may be allowed to indicate whether they wish toparticipate in an automated savings notification program, e.g., whetherthe client would like to learn of a recommendation that suggests a wayto save a specified amount in billing charges. In such an embodiment,the client 148 may for example indicate to the pricing optimizer 181that the client 148 only wishes to receive recommendations that couldsave the client at least $5,000 (or some chosen amount) over a specifiedperiod of time. Clients 148 may also indicate other types ofpreferences, such as the types of resource usage and/or billing data theclient is willing to provide for pricing optimization purposes, theintervals at which the resource usage data is collected, the methods(such as web-based notifications, social media-based notifications,email notifications or the like) the pricing optimizer should use tonotify the client regarding recommendations, in some implementations.

The pricing optimizer 181 may obtain past and current pricing data 303for various types of resource instances, as well as the billing amountsthat were charged to the specific client or clients 148 for whom arecommendation is being developed. Historical pricing data could forexample be obtained from the resource management database 191, and/orfrom a separate billing database, in some embodiments. The pricingoptimizer 181 may use historical pricing and billing data gathered forvarious time periods to estimate future billing amounts (assuming thesame trends continue) for a given client 148 in one embodiment, and mayprovide such anticipated trends, as well as historical billing and usagedata to the clients via a programmatic interface. For example, based onpast usage and billing, the pricing optimizer may be able to inform aclient that the client's costs are likely to rise by X percent over thenext Y months, which might make the idea of receiving recommendationsthat could lower bills more attractive to the client.

In some embodiments, one or more provider-side metrics agents 140 mayserve as sources of resource usage data for a given client 148. Suchagents may be instantiated at various points in the provider network110, and may be used for multiple purposes—e.g., for monitoring theprovider network's resources over time to ensure that the resources arefunctioning and performing in desired operation ranges, to help generatebilling information that may be based on usage, as well as to provideinputs to the pricing optimizer 181. Various kinds of usage data may begathered for a given client 148, such as the types and sizes ofinstances reserved and used, the uptimes of the instances, the operatingsystem and other software elements in use, IP addresses, CPUutilizations, memory utilizations, I/O rates, I/O device utilizations,network transfer rates and network device utilizations, and so on.Performance and uptime related usage metrics may help the pricingoptimizer decide the specific instance types to recommend for theclient—e.g., whether large vs. medium vs. small instances should berecommended, and/or whether, for reserved instances, high-uptime ratiovs. medium uptime-ratio vs. low-uptime ratio instance should berecommended.

Clients 148, or potential clients of the provider network 110 who wishto learn about savings that might accrue if they decide to use theresource instances of the provider network 110, may in some embodimentsallow resource usage data to be gathered from client premises, clientnetworks, and/or client data centers. In one embodiment an installableclient-side metrics agent 190 may be made available to the client orprospective client. After the client-side metrics agent 190 is installedand activated, it may gather and transmit usage data to the pricingoptimizer 181, e.g., in accordance with the preferences specified by theclient or prospective client. In some implementations, the gatheredinformation may first be provided to the client 148 for approval, beforeit is transmitted to the pricing optimizer, so that the client isassured that sensitive data is not transmitted to the pricing optimizer.Client-side metrics agents 190 may gather information such as clientdevice resource specifications (e.g., server vendors and models, CPUmodels and speeds, memory sizes etc.), in addition to the types of datagathered by provider-side metrics agents 140. In some embodiments thetypes of hardware and/or software stacks being used at client premisesor data centers may differ from the types of hardware being used forresource instances 130 of the provider network 110. For example, theclient may use a different server vendor that provides servers using adifferent CPU type or processor architecture than the provider networkdoes. In such cases, the pricing optimizer 181 may also be required tomap or translate resource usage data gathered from the client'shardware/software combination to units that are useful in determiningthe equivalent number and type of resources of the provider network'shardware/software combinations. For example, the client might usehardware vendor A's servers, each of which uses N CPUs of type K, whilethe provider network uses hardware vendor B's servers, each of whichuses P CPUs of type L. CPU utilization and other data gathered from theclient's servers in such an example may need to be transformed ormodified (e.g. using ratios of results of industry standard performancebenchmarks that have been run on both types of CPUs) to determineequivalent metrics at the provider network's instances 130.

Using the various sources of information shown in FIG. 3, the pricingoptimizer may generate recommendations 351 for various instanceoperations (such as future long-term reservations, suggested resellingof existing reservations, future use of on-demand instances or spotinstances, and so on) that the client 148 should perform to obtain thebest value for the client's budget. In one implementation, for example,a client may have reserved one or more large instances (i.e., instanceswith a high performance capability rating). Based on factors such as theactual resource usage by the client and the uptimes of the reservedlarge instances, which may show that the client does not typically usemuch of the reserved compute capability of the large instances, thepricing optimizer 181 may suggest in the recommendation that smallerinstances should be used instead of large instances, thereby potentiallyreducing the client's billing costs while still accomplishing thecomputation goals of the client. In implementations where the resale ofexisting reservations is supported, the pricing optimizer 181 may inthis example recommend that the large reserved instance slots be resold,and that slots for smaller reserved instances be obtained instead. Therecommendations 351 may be transmitted to the client 148 in accordancewith the client's notification preferences—e.g., using a webnotification, social media, email, and/or a combination of notificationoptions.

Example Web-Based Interfaces for Pricing Optimizer Interactions

FIG. 4 illustrates a portion of an example web-based interface that maybe used to display past usage and billing information of a client'sresource instances, according to some embodiments. As shown, theinterface may comprise a web page 400 including a number of differentregions. The web page 400 may include a welcome message area 403 and oneor more filtering options 405 allowing a client to select the instancetypes (e.g., reserved instances vs. on-demand instances vs. spotinstances), availability zones, and any other appropriate searchfiltering parameters. Drop-down options may be provided for thefiltering choices in some implementations, so that a given client 148viewing page 400 may select from the relevant subset of choices thatapply specifically to that client.

A graphical display region 407 may show, for example, the number ofinstances of different types that were used by the client (in accordancewith the filtering options specified) during a particular period oftime. In the illustrated graph, three lines are shown in region 407, oneline each respectively representing usage of reserved instances,on-demand instances, and spot-instances. In some implementations asecond graphical region 411 may show corresponding billing amounts forthe different types of instances 130, over one or more billing periodsthat may correspond to the time range shown in the usage graph. Variousother techniques to represent usage and/or billing amounts (e.g., piecharts, superimposed maps, and the like) may be utilized in differentimplementations of the usage history interface.

In one embodiment, a web page similar to web page 400 may allow theclient 148 to indicate whether the client wishes to utilize the servicesof a pricing optimizer 181. For example, in FIG. 4, the client mayselect from the answers “Yes”, “No” and “Tell me more . . . ” to respondto the question “Would you like to use our pricing optimizer to loweryour bills” in region 415. If the client selects the “Tell me more . . .” option, details regarding the functionality of the pricing optimizer181 may be displayed. Similarly, a client may be allowed to indicatewhether the client wishes to participate in an automated savingsnotification program in some implementations. If the client elects toparticipate in an automated savings notification program, the client mayspecify a minimum saving amount that the pricing optimizer should use todetermine whether a notification of recommended actions is to be sent tothe client. As shown, the client may select from among the answers“Yes”, “No” and “Tell me more . . . ” to respond to the questionregarding automated savings notifications in region 419 of web page 400.If the client selects “Yes” to either question, a different page may bedisplayed allowing more details to be shown regarding the services theclient wishes to use. The button labeled “Continue” may be used by theclient to progress to the next part of the interface after the answersto the opt-in questions of regions 415 and 419 are answered. Variousportions of the web page 400 may be arranged differently, and may bedisplayed as parts of several different pages, in differentimplementations. In some embodiments usage information may be aggregatedfor multiple clients and displayed together (e.g., if a largecorporation wishes to view usage history for multiple individual usersof provider network 110).

FIG. 5 illustrates a portion of an example web-based interface that maybe used by a client to specify preferences to pricing optimizer 181,according to some embodiments. The web page 500 shown in FIG. 5 may bedisplayed after a client 148 makes an initial decision to opt in for theservices provided by pricing optimizer 181 (e.g., by selecting the “Yes”option in region 415 of FIG. 4). In the illustrated example web page500, region 503 may include a message to the client asking the client toprovide as many preference details as they wish to provide.

Region 507 of web page 500 may include a number of form fields that theclient 148 may fill out. One field 509 may, for example, allow theclient to specify a target budget that the pricing optimizer may use asan optimization constraint. A default selection value indicating thatthe client does not wish to specify an exact budget, but does wish tominimize its bill, is shown in the target budget value field 509 in FIG.5. In some embodiments, instead of or in addition to a budget-relatedtarget, a client may specify an instance count availability target,e.g., a particular client may wish to ensure that at least N largecompute instances be reserved. An instance count availability targetfield 510 may be provided for clients to specify such instanceavailability-related targets in such embodiments. The client may use afield 511 to specify preferences for availability zones in someimplementations. In some embodiments, if the client does not specifyavailability zones or other location-related preferences, the pricingoptimizer may utilize IP address information obtained from theprovider-side and/or client-side usage metrics agents to determine themost appropriate availability zones or locations to suggest in itsrecommendations. For example, each instance 130 of the provider networkmay have one or more IP addresses whose availability zone and/orgeographical region may be deduced or obtained by the pricing optimizer.Similarly, physical locations for client-side IP addresses may be lookedup or provided by the client, thus allowing the pricing optimizer tochoose the most appropriate availability zones/regions for therecommended resource instances, e.g., based on proximity to the clientresources.

Client preferences for instance types (e.g., reserved vs. on-demand) maybe specified via a field 513 of region 507 in some embodiments.Interruptibility setting preferences (e.g., do-not-interrupt vs.fully-interruptible) may be specified using a field 515, and instancesize or performance rating preferences may be specified via a field 517.The client's interruptibility preferences may be usable by the pricingoptimizer to select the specific instance pool for one or morerecommended instances in some implementations (especially in embodimentswhere multiple interruptibility settings are supported, as describedbelow in greater detail). In some implementations a client may be ableto provide the pricing optimizer with information about an expectedchange in demand—e.g., if the client is aware that an aggressiveadvertisement strategy may result in a greater load on the instancesthat the client uses for its e-commerce website within a month, suchinformation may be provided to the pricing optimizer using a fieldsimilar to field 519 shown in FIG. 5. Field 519 or similar fields mayalso be usable by the client to specify various “what-if” scenarios,e.g., to find the kinds of recommendations the pricing optimizer mightdevelop based on various workload scenarios (such as a 100% increase incompute demand) that may or may not actually arise. The client may alsoprovide preferences regarding the mechanism(s) to be used to providerecommendations (e.g., via e-mail, social media notifications, and soon) using a field 523, and the preferred frequency or schedule withwhich the recommendations are to be provided via a field 521. Variousother client optimization preferences may be provided in differentimplementations. Default values for some or all of the preferences maybe used by the pricing optimizer if the client does not provide specificpreferences in some embodiments.

FIG. 6 illustrates a portion of an example web-based interface that maybe used to provide one or more instance recommendations, according tosome embodiments. After receiving an indication that a particular client148 wishes to utilize its services, and after obtaining the client'soptimization goals and preferences as well as the inputs needed fromother source shown in FIG. 3, the pricing optimizer may perform variouscomputations needed to arrive at some recommended set of actions for theclient to take. The results of these computations, which may be based onone or more heuristics or algorithms implemented by the pricingoptimizer 181, may be displayed to the client via a web page similar toweb page 600 in some implementations.

As shown, web page 600 may comprise a message region 603 in which thepricing optimizer informs the client 148 that a recommendation has beengenerated. A region 607 may comprise various details of arecommendation. For example region 607 may include an indication of atime period covered by the recommendation (e.g., a start time and a stoptime, such that the actions in the recommendation should be madeeffective during the period between the start and stop time). Inimplementations where availability containers such as availability zonesare used, the recommendations may be grouped by availability zones. Foreach availability zone in such an implementation, the number, size,type, uptime ratio and various other details for the instances 130 thatthe client 148 should obtain may be indicated. In some embodiments, asnoted above, the pricing optimizer may determine target availabilityzones for various recommended instances based on the analysis of IPaddresses used by the clients, as indicated in usage records collectedfor the client. The IP addresses might indicate geographical locationswhere the client has used equipment in the past, which may in turn behelpful in selecting the data centers and corresponding availabilityzones appropriate for the client.

In the illustrated example, the price of each line item (i.e., each setof like instances) may also be displayed, as well as the total billassociated with the reservation. In some embodiments, the pricingoptimizer may allow the client to specify whether the client wishes tohave the recommendation implemented automatically, e.g. withoutobtaining additional consent from the client for one or more recommendedactions. In the example shown in FIG. 6, the client may opt-in for suchan automated recommendation implementation by selecting the “Yes” optionin response to the question “Would you like us to allocate theseinstance automatically?” in region 609. In some implementations theinterface may allow the client 148 to request a viewing of a graphicaldisplay of the recommendation (e.g., via button 613 of FIG. 6). A button615 may allow the user to return to the pricing optimizer's home page.

FIG. 7 illustrates a portion of an example web-based interface that maybe used to display projections of future resource usage, according tosome embodiments. In the illustrated web page 700, the pricing optimizerdisplays anticipated future usage and billing for a particular client148, e.g., based on analysis of the client's earlier usage records. (Theillustrated example shows projections based on the trends observed inthe client's usage history, prior to implementing any suggestedrecommendations. Similar graphical displays of the results ofrecommendations may also be shown in some embodiments, e.g., as a resultof a client clicking on button similar to button 613 of FIG. 6).

As shown, the web page 700 includes a message area 703 indicating to theclient that the page shows projected usage based on analysis of someperiod of past usage. The types of instances 130 and availability zones120 for which the projections are shown may be selected using filteringoptions 705 in some implementations. One display area 707 may show agraphical representation of the expected use of various types ofinstances over some future period, and a second display area 711 mayshow the corresponding expected billing amounts in some implementations.The client 148 may be allowed to indicate whether they wish to use theservices of the pricing optimizer, e.g., by responding affirmatively tothe question shown in region 715. In some implementations the client maybe given the opportunity, e.g., via response to the question shown inregion 719, to opt for an automated savings notification program similarto the one discussed earlier in conjunction with the description of FIG.4. Button 723 may allow the client to proceed to the next step in theinteraction. Variations of the types of web pages shown in FIG. 4-FIG. 7may be implemented in different embodiments. Some of the elements shownwithin a single web page may be separated into two or more interactions,or elements shown in multiple web pages may be combined into one webpage. Interfaces other than web pages, such as installable thin clients,APIs, or command-line tools may be used in other embodiments.

Methods to Implement Pricing Optimizer Functionality

FIG. 8 is a flow diagram illustrating aspects of the functionality of apricing optimizer, according to at least some embodiments. As shown inelement 801, resource usage records of a client or prospective clientsmay be obtained from one or more usage data sources, for example fromprovider-side metrics agents 140 and/or client-side metrics agents 190.Various kinds of usage information, such as the number and types ofresources used, the specific hardware/software stacks used, the uptimes(periods during which the resources were activated), CPU utilizations,I/O rates and device utilizations, network transfer rates and deviceutilizations, IP addresses, and the like, may be gathered either fromwithin the provider network, or from the client network, or both. Insome embodiments the usage data may be transmitted directly from variousmetrics agents to the pricing optimizer, while in other cases the usagedata records may be stored in a repository such as the resourcemanagement database 191, and may be retrieved as needed by the pricingoptimizer. In some implementations monitoring tools that may be includedwithin installed software components on various resource instances, suchas operating system-provided performance monitors or tools, may be usedto gather at least a portion of the usage data.

As shown in element 805, pricing information on various types ofinstances may be obtained, for example from the resource manager 180and/or a price history database that may in come implementations beincluded in the resource management database 191. The pricinginformation may be gathered for some recent time period, such as theprevious month or the previous three months; the length of the periodmay be configurable in response to client preferences in someimplementation. By combining portions of the pricing information withresource usage information, the actual amounts billed to a given clientmay be computed in some implementations. In other implementations theclient's billing history may be obtained. In embodiments where billingrecords and usage records are both obtained, billing and usage data maybe cross-checked for mutual consistency.

The client's optimization goals and preferences may be obtained as wellin some embodiments, as shown in element 809. In some implementationsthe goals and/or preferences may be obtained via a programmaticinterface, examples of which are illustrated in FIGS. 4 and 5. Defaultgoals such as a general desire to reduce costs may be used if specificgoals and/or preferences are not provided by the client. Taking theusage data, the pricing data, and the goals/preferences into account,one or more recommendations regarding future instance use may begenerated, as shown in element 813 of FIG. 8, and a notification of therecommended action(s) may be provided to the client (element 817).Recommendations may include any combination of a wide variety ofsuggested actions, such as actions to acquire or reserve instances, toresell existing reservation slots, to substitute one reservation foranother in a different availability zone, to use different sizes ofinstances, to use spot instances instead of longer-term allocations, andso on.

In some embodiments clients may be given the opportunity to installclient-side metrics agents 190 at client devices and/or in clientnetworks to help provide input to pricing optimizers 181. FIG. 9 is aflow diagram illustrating a subset of the functions of a pricingoptimizer 181 relating to the use of a client-side metrics agent 190,according to at least some embodiments. As shown in element 901 of FIG.9, a programmatic interface such as one or more web pages or web sitesmay be implemented, allowing clients to submit a request to obtain aclient-side metrics agent to gather data that may be usable by a pricingoptimizer to generate recommendations. When such a request is received(element 905), a download of the client-side metrics agent software maybe initiated in some implementations. In other implementations thesoftware for a client-side metrics agent may be transmitted using othermeans, such as a DVD or a CD which may be provided to the client. Thesoftware may for example include one or more executable programs orscripts that enable the monitoring of resource usage and thetransmission of the gathered data back to the pricing optimizer 181 orto some intermediary (e.g., a resource manager 180 or a resourcemanagement database 191) from which the pricing optimizer 181 can obtainusage records.

The success of the download and/or installation of the client-sidemetrics agent 190 may be verified in some embodiments (element 909) andone or more tests may be run to verify that the agent is workingcorrectly. For example, in one implementation one or more shortcompute-intensive tests may be run on a client's compute server, and theCPU utilization data gathered by the client-side metrics agent 190during the test run may be sanity checked. In some embodiments multiplecopies or instances of the client-side metrics agent 190 may beinstalled at various devices or entities of the client's data centers,and the functionality of some subset or all of the instances or copiesmay be checked. After the functionality and connectivity of theclient-side metrics agent is verified, collection of usage records ofthe client-side resources may begin (element 913).

In some environments the client-side resources may differ from theresources used for the provider network's resource instances 130. Forexample, compute servers used in the client's data centers may employCPUs with a different architecture and clock speed, or the client'ssystems may use a different operating system. In such environments, themeasurements included in the client-side usage data records may have tobe translated or mapped into their approximate equivalents with respectto the provider network's resource instances (element 917). For example,using either externally published benchmark results or proprietaryperformance test results, the pricing optimizer 181 in one embodimentmay determine that if the execution of a given workload on aclient-owned CPU C1 from vendor V1 results in a CPU utilization of 50%,an equivalent workload when run on a CPU C2 used at a resource instance130 of the provider network may result in a CPU utilization of 75%. Suchmappings of client-side resource characteristics and capabilities toprovider-side resource characteristics and capabilities may be helpfulin generating useful recommendations.

FIG. 10 is a flow diagram illustrating aspects of the functionality of apricing optimizer 181 that implements a programmatic interface allowingclients to indicate optimization preferences, according to at least someembodiments. As shown in element 1001, a programmatic interface such asa web page, an API or a command-line interface may be implemented. Usingthe interface, a client or a prospective client may indicate varioustypes of optimization goals or desired instance attributes. For example,high-level goals may include a desire to spend no more than a targetbudget amount for resources during a given period of time, or a desireto save a specified amount compared to a previously-incurred billingamount. More specific, lower-level goals or preferences indicated by theinterface may include, for example, preferred instance sizes,availability zones, geographical regions, instance interruptibilitylevels, installed software programs or program versions, and so on.

The pricing optimizer 181 may receive one or more indications of aclient's optimization goals and/or preferences formatted according tothe interface (element 1005) and use the goals or preferences, togetherwith resource usage records, to develop recommendations and projectionsof future usage and costs (element 1009). In some implementations therecommendations and/or projections may be provided to the client 148using additional elements of the same interface (element 1013). In otherimplementations one or more different techniques or interfaces may beused to notify the client regarding recommendations—for example, clientsmay specify their goals and preferences via a web interface but mayreceive recommendations via e-mail.

In one embodiment, portions of the services provided by the pricingoptimizer 181 may be exposed to third parties (i.e., entities other thanthe clients 148 which directly utilize the resource instances 130 of theprovider network 110). Intermediaries such as resource managementsoftware vendors or resellers of the provider network's resources mayfor example wish to provide guidance to their own clients on how best tomanage their resource budgets. FIG. 11 is a flow diagram illustratingaspects of the functionality of a pricing optimizer 181 that implementsa programmatic interface (such as an API, a command-line interface or aweb-based interface) supporting third-party interactions, according toat least some embodiments. As shown in element 1101, third-partyentities may be allowed to provide inputs to, and/or receive outputsfrom, the pricing optimizer 181 using such an interface in someembodiments. In some implementations, for example, an API may be exposedto third party providers that implements a subset or all of thecapabilities exposed to clients 148 via web pages, e.g., resource usageand billing history may be made available via the API, optimizationgoals and preferences may be expressed via the API, and so on. In someimplementations client-side metrics agents may be made available forthird parties to utilize at client-side premises or third-partypremises.

In some embodiments where the third party provider intends to build oneor more tools or extensions based on the services provided by thepricing optimizer 181, the provider network operator may wish to retainthe right to approve/disapprove the extensions or tools, so that forexample the brand name of the provider network is not affectednegatively by a poorly implemented tool or extension. In such anembodiment, the third-party provider's client-facing tools or extensionsmay require approval before being made available to its clients (element1105). Various optimization-related requests, such as requests toprovide projections of future resource use by a client (e.g., a clientof the third-party provider that also uses instances 130 of the providernetwork 110) based on past use, or a request for recommended instanceactions to reduce billing, may be received via the third-party interfacein some embodiments (element 1109). Responses to theoptimization-related requests may be provided in accordance with theprogrammatic interface (element 1113).

Automated Instance Acquisition Actions

In some embodiments, a client 148 may decide to opt in for a servicethat automatically implements recommendations generated by the pricingoptimizer. FIG. 12 illustrates example interactions that may occurbetween a client 148 and the resource manager 180, and between thepricing optimizer 180 and the resource manager 180, to implementautomated reservation optimization actions, according to one embodiment.As shown, the client may transmit an indication 1205 that the client hasopted in for automated implementation of recommendations (either for aspecified subset of the client's instances 130 or for the entire set ofinstances 130 used by or reserved for the client). The pricing optimizer181 may be operable to provide instance action recommendations 251,generated on behalf of the client based on the kinds of inputs 1201illustrated in FIG. 3 (such as client resource usage, optimization goalsand preferences, and pricing information), directly to the resourcemanager 180 instead of (or in addition to) notifying the client 148.

In response to receiving an indication of one or more recommendedactions, the resource manager 180 may proceed to put the recommendationsinto effect, without any further requests from the client. For example,in the embodiment illustrated in FIG. 12, the automated reservationactions 1210 may include a listing of an instance currently reserved forthe client 148 in a reservation resale marketplace, reselling suchlisted instances if a buyer is found, obtaining different reservations(potentially in different availability zones) on behalf of the client,acquiring on-demand and/or spot instances, and the like. In someembodiments the resource manager may inform the client 148 when eachrecommended action is completed, e.g., via an e-mail or othernotification, while in other embodiments the a summary of the set ofautomated actions taken on behalf of the client 148 may be provided atsome designated intervals such as once a billing period or once a month.In some implementations the client may be able to specify schedulingpreferences for when the automated action should be performed. Forexample, the client may indicate that automated actions may be performedat most once a week (e.g., Mondays between 1 AM and 2 AM), or that noautomated actions should be performed during some specified timeinterval, and so on. In such implementations, the resource manager 180may perform automated actions in accordance with the client's schedulingpreferences. As noted earlier, one scheduling option or preference(which may in some cases be the default) is that the resource manager isallowed to perform the automated actions at any time of its choice. Inone embodiment, the resource manager may also provide an indication tothe client of the actual vs. predicted costs—e.g., if the pricingoptimizer 181 suggested in the recommendation that the billing costs fora quarter could be reduced to $X, the resource manager may implement theactions and at the end of the quarter show the client how closely thepredictions matched the actual costs. Of course, in addition toautomated implementation of recommendations, the resource manager 180may also perform a number of types of operations explicitly requested bythe client, e.g., reserving a set of instances, obtaining on-demand andspot instances, and the like.

FIG. 13 illustrates a portion of an example web-based interface that maybe used by a client 148 to opt-in to a service providing automatedreservation optimization, according to some embodiments. As shown, theinterface may include a web page 1300 that includes a welcome messagearea 1303 and one or more graphical display regions 1307 and 1311showing usage history and billing history of the client. The types ofinstance and the specific availability zones for which usage historyand/or billing history is displayed may be selectable using filteringoptions 1305 in some implementations. In the illustrated interface, theclient may indicate that it is willing to sign up for automatedimplementation of recommendations by selecting the “Yes” response to thequestion posed in region 1315. In some implementations, the client mayalso indicate additional optimization constraints, such as a targetbudget limit, a preferred schedule, and the like, using elements of theinterface such as the form field 1319 (or a collection of form fieldssimilar to some of the fields illustrated in FIG. 5). A control elementsuch as button 1323 may be used to proceed to the next step of enrolmentin the automated recommendation implementation service, where forexample the client 148 may specify the frequency with whichnotifications regarding completed automated actions should be sent, themechanism to be used for such notifications, and so on.

In some embodiments a client 148 may be able to specify that it wishesto utilize the automated service for some subset of the client'sinstances, but not all of the client's instances. In one implementationadditional settings for different subsets of potential automated actionsmay be specified by the client: e.g., the client may be able to indicatethe equivalent of “If the recommended action involves obtaining asubstitute reservation at a lower price, go ahead and implement theaction automatically; but if the action involves purchasing additionalinstances, notify me and obtain my approval before purchasing theadditional instances”. In some embodiments the client may be able to seta budget limit for automated actions that require no pre-approval—e.g.,the client may be able to indicate the equivalent of “If the recommendedaction is going to make a change to my billing amount of no more than$1000, implement the action; but if the billing impact is going to begreater than that, please obtain my consent before implementing therecommendation”. The level of authority granted to the resource manager180 to make recommended actions without additional approvals by theclient may thus vary in different implementations.

Methods for Automated Implementation of Reservation Recommendations

FIG. 14 is a flow diagram illustrating aspects of the operation of aresource manager 180 supporting automated implementation ofrecommendations for reserved instance operations, according to at leastone embodiment. The resource manager 180 may receive an opt-inindication from a client 148 for automated reservation optimization(element 1401 of FIG. 14), e.g., via a programmatic interface such as aweb page similar to that shown in FIG. 13, or via some othercommunication mechanism such as an e-mail. The fact that the client 148has opted in may be communicated to the pricing optimizer 181, and thepricing optimizer 181 may begin collecting resource usage data, pricingdata, and any other information pertinent to making recommendations forthe client 148. In some embodiments the client 148 may, in addition toopting in for the automated service, provide specific optimization goalsand preferences to be used in making the recommendations. In someimplementations a specific set of client instances for which recommendedactions are to be automated may be indicated by the client; in otherimplementations, by default or in response to an indication from theclient, all of the client's resource instances may be considered forautomated actions. In one implementation, a client 148 or a potentialclient 148 that does not currently have any allocated or reservedinstances 130 in the provider network 110 may opt-in for the automatedservice, so that the entire set of resource instances acquired for theclient may be acquired as result of automated recommendation actions.

The resource manager may wait for the next recommendation provided bythe pricing optimizer (element 1405 of FIG. 14). The timing ofrecommendations may vary in different implementations, and may bedependent on preferences specified by the client 148, the complexity ofthe computations involved in making the recommendations, which may inturn depend on such factors as the total number and types of instances130 that the client uses. For example, in one embodiment the pricingoptimizer 181 may provide a set of recommendations every month or everyweek based on a client preference, while in another embodiment thetiming of recommendations may depend on the amount of savings that thepricing optimizer can find—e.g., if the maximum potential savings foundduring a particular analysis by the pricing optimizer is less than$1000, no recommendation may be generated.

In the embodiment illustrated in FIG. 14, some of the types ofrecommended actions could include suggested listing ofcurrently-reserved instances in an instance reselling marketplace,acquisition of additional or replacement reservations, and the like. Ifa recommendation from the pricing optimizer 181 suggests that one ormore currently reserved instances should be resold (as determined inelement 1409), the resource manager 180 may list the one or moreinstances for resale (element 1413). In some implementations therecommendation could identify the specific reserved instances or slotsthat should be resold, while in other implementations the number andtype of reserved instances to be resold may be specified in therecommendation (e.g., the recommendation may suggest the equivalent of“Resell 2 large, medium uptime ratio instances in availability zone X”)and the specific reservations that are resold may be selected by theresource manager 180. If, in addition to reselling an instance orinstances the recommendation also recommends the acquisition of one ormore additional reservations (as determined in element 1414), theresource manager 180 may verify that the recommended number of instancesis still available, and reserve that number of instances (element 1415).Such a verification may be needed, for example, because some time mayhave elapsed between the generation of the recommendation and the timeat which an attempt to reserve the additional instances occurs; thus, itmay be possible in some cases that the desired number of reservationscannot be made. In some embodiments, if the desired number of additionalinstances cannot be acquired, the client may be informed. Various othererror/corner cases may also have to be dealt with by the resourcemanager 180 in some embodiments.

Depending on the demand for instances of the type being resold, and thepricing policies associated with the listings, it may take some timebefore a buyer is found for the listed instances. For example, thelistings on the resale marketplace may have a minimum price associatedwith them, and buyers may not necessarily be willing to pay the minimumprice for at least some time period. The resource manager 180 may waitfor a resell-related event that causes the instances to be removed fromthe listing (element 1417 of FIG. 4). Such an event could include, forexample, an actual resale of the listed reserved instances to anotherclient (as determined in element 1421), or in some cases the instancesor reservation slots could be delisted at the request of the currentowner client 148 or as a result of a new recommendation from the pricingoptimizer 181. For example, if the instances remain unsold for a while,the client's resource demand may increase, or the market price forresold instances may decline sufficiently that it may no longer bebeneficial to resell the instances. In response to a determination thatdelisting is beneficial, the resource manager 180 may therefore removethe instances or reservation slots from the resale listing (element1437) and return the instances to the client's reserved instance set. Ifthe instances/slots are resold, they may be delisted and removed fromthe client's reserved instance set (element 1425). In someimplementations, the listed instances may remain in the currentreservation set of the client until they are actually resold.

If the recommendation does not suggest resale of reserved instances (Asdetermined in element 1409), it may include a suggestion for additionalreserved instances, or acquisition of different (e.g., cheaper) reservedinstances than the ones the client currently has. If such additionalreservations are recommended (as determined in element 1429), theresource manager 180 may verify that the instances are available forreservation as discussed above with reference to element 1415, and mayacquire the suggested additional reservations for the client (element1433). In some implementations, as noted above, a single recommendationmay include suggestions for reselling some reserved instances andacquiring other reservations—for example, based on the relative pricingof different sets of reserved instances in different availability zonesor regions, the availability and pricing of instances listed on thereserved instance reselling marketplace, and so on. After therecommended reservation-related actions specified in one recommendationare taken, the resource manager may again wait for the nextrecommendation (element 1405).

In some embodiments, an interface manager 182 or a subcomponent of aresource manager 180 may implement one or more programmatic interfacesfor interactions related to automated implementation of the pricingoptimizer's recommendations. FIG. 15 is a flow diagram illustratingaspects of the operation of a resource manager 180 configured to providea programmatic interface to allow clients 148 to opt-in for automatedinstance trading based on recommendations from a pricing optimizer,according to at least one embodiment. An interface such as one or moreweb pages (e.g., pages similar to web page 1300 of FIG. 13), APIs orcommand-line interfaces may be implemented to receive the opt-inindication (element 1501 of FIG. 15). In some embodiments portions ofthe interface may also allow clients to specify optimization goalsand/or preferences. The resource manager may receive an indication of anopt-in by the client, and any other goals and preferences specified viathe interface (element 1505).

The pricing optimizer 181 may then be notified that recommendationspertinent to the client should be generated (element 1509). In somecases additional communications with the client 148 may also berequired—e.g., the client 148 may be advised to download or obtainclient-side metrics agents 190, and/or agree to monitoring of theclient's resource usage; such additional communications may also be madein accordance with the programmatic interface in some embodiments. Theresource manager 180 may then wait for the next recommendation generatedby the pricing optimizer (element 1513). After a recommendation isreceived, the resource manager 180 may implement one or more of therecommended actions (element 1517), and in some embodiments may informthe client 148 that the actions have been implemented using portions ofthe programmatic interface.

Support for Enhanced Interruptibility Levels

At any given point in time, many of the resource instances 130 of aprovider network 110, including instances that have been reserved inadvance or have already been allocated to clients 148, may be idle orinactive. Such idle instances may represent a dynamically changing poolof surplus capacity, which can potentially be monetized in a number ofdifferent ways. In one simple example, an idle instance for which areservation currently exists may be listed in a spot-instance market,i.e., it may be offered at a reasonably low price on the condition thataccess to it may be revoked whenever the corresponding reservationholder requests access to the instance. Depending on the nature of theapplication being run, such interruptible instance allocations may beacceptable to various types of clients—e.g., clients that runcomputations that can be broken down into phases such that theinterruption or stoppage of the application during any one phase doesnot affect the results of other phases, or clients that runshort-transaction workloads where a failure of a small number of shorttransactions can be remedied simply by rerunning the transactions. Sometypes of client applications or workloads may consist of phases ortransactions with different levels of sensitivity to interruptions—somephases of the workload may be interruptible without having to do a lotof rework, other phases or transactions may require at least some noticeto save state in order for the application to be resumed withoutexcessive overhead, while other phases may require substantial rework ifthey are interrupted. In some embodiments the resource manager 180 maysupport several different levels of resource instance interruptibility,to more effectively cater to the varying interruptibility-related needsof clients, and at the same time generate revenues for the providernetwork operator by utilizing resources that would otherwise be idle.

FIG. 16 illustrates an embodiment in which a resource manager 180 mayfulfill requirements for any of a plurality of levels ofinterruptibility using a dynamically sized set ofenhanced-interruptibility available instances. In the illustratedembodiment, system 1600 comprises a plurality of instances 130, each ofwhich is assigned to an instance pool. Each instance 130 may have anassociated interruptibility property or setting indicating theconditions under which access to the instance may be revoked by theresource manager 180. Instances 130 that are currently active (i.e.,accessible via the network, performing functions, running applications,and/or providing services to various clients 148), which may be termedin-use instances 1601, may be organized into several pools such as areserved instances pool 1605, an on-demand instance pool 1609, and oneor more interruptible instance pool(s) 1613 such as a spot instancepool. Instances that are currently not in use may be assigned to anavailable instance pool 1625 with a baseline or default interruptibilitylevel. A subset of the instances of the available instance pool 1625 maybe assigned to one or more enhanced-interruptibility sub-pools 1617,i.e., the current or potential interruptibility setting of theseinstances may differ from the baseline interruptibility setting for theavailable instances outside the sub-pools. Details on how instances aremoved in and out of the various pools and sub-pools, e.g., in responseto actual and/or anticipated supply and demand, and the different levelsof enhanced interruptibility that may be supported in differentembodiments are provided below.

At any given point in time, some instance reservations may exist forwhich the corresponding instances are not currently in use; suchcurrently unfulfilled reservations are represented in FIG. 16 by slots1621. System 1600 may also include a pricing optimizer 181 and aresource management database 190. The pricing optimizer 181 may beoperable to perform enhanced optimization operations and/or generaterecommendations that take multiple interruptibility levels into account,in addition to performing the core pricing optimizer functions describedearlier. The resource management database 190 may be used to storevarious types of instance information, including pricing information,performance capacity information, usage records, and interruptibilitysettings of various resources. It is noted that although availabilityzones are not shown explicitly in FIG. 16, each of the instances shownmay in some embodiments belong to an availability zone and/or ageographic region of a provider network; for example, all the instances130 shown in FIG. 16 may belong to the same availability zone.

As described earlier, clients 148 may reserve resource instances foragreed-upon reservation periods such as one-year terms or three-yearterms in some embodiments. When a client 148 makes such a reservation,the resource manager 180 is committed to provide access to a resourceinstance with the specified performance capability and othercharacteristics, whenever the client requests such access during theterm of the reservation. However, this does not mean that the client 148necessarily has all its reserved instances in an active state (e.g.,with the instance's operating system booted, various applicationsrunning and/or accessible via the network) at any given point in time.For example, the client 148 may wish to activate some subset of itsreserved instances only when the client workload reaches a thresholdlevel, thereby potentially avoiding having to pay unnecessaryusage-based billing amounts (since some types of reservations may incurboth up-front reservation fees and fees based on actual hours or minutesof usage). In FIG. 16, the reserved instance pool 1605 of the in-useinstances 1601 represents the set of currently active reservedinstances, e.g., instances 130A and 130B, of the clients 148. Thecurrently unfulfilled reservations of various clients are represented byslots 1621. Whenever a client 148 that owns one of the unfulfilledreservation slots requests access to an instance, a currently availableinstance may be provided—e.g., one instance from available instance pool1625 may be moved to reserved instance pool 1605, and the number ofunfulfilled reservation slots 1621 may be decremented accordingly.

To support the commitment made by the resource manager to providenear-immediate or immediate access in response to fulfillment requestsfor reservation slots, a default interruptibility level may be assignedto some subset of the instances (such as 130G, 130H, 130I, 130J) of theavailable instance pool that are set aside to meet the demand forreserved slots. The default interruptibility level may for exampleindicate that the resource manager may revoke access to the instance atany time and without providing any notice of access revocation. Such aninterruptibility level may be termed“interruptible-without-notification” herein. The pricing forinterruptible-without-notification instances may also vary over time,depending for example on the relative demand for various levels ofinterruptibility and the supply of available instances. When a clientsubmits an acceptable instance acquisition request for aninterruptible-without-notification instance (e.g., if the client's bidfor the instance meets the current price for such instances), aninstance of the requested type may be allocated to the client, and theinstance may be assigned to an in-use interruptible instance pool 1613.The total number of interruptible-without-notification availableinstances to be kept either as a reserve in the available pool, or inone of the interruptible in-use instance pools 1613, may be determinedby the resource manager at least in part on the number of outstandingunfulfilled reservations at any given time. For example, if there areten currently unfulfilled reservation slots, in one implementation theresource manager may wish to ensure that there are at least ten suitableinstances than can be interrupted without notification (i.e., that thesum of the number of in-use immediately interruptible instances and thenumber of interruptible-without-notification instances in the availablepool is at least ten), to handle any sudden burst of reservationfulfillment requests. Instances may be moved in and out of the variouspools and sub-pools based on projected demand for reserved instances insome embodiments.

Other factors, such as the anticipated rate of requests for on-demandinstances, may also influence the number ofinterruptible-without-notification instances in the available pool. Anon-demand instance, as described above, may not require a long-termreservation; clients may typically use on-demand instances when they donot wish to pay the upfront fees required for long-term reservations,but do want more stability in instance pricing (and/or lessinterruptibility) than may be typically possible for spot instances.While the operator of the provider network may not be able to guaranteethat all requests for on-demand instances will necessarily be met, theoperator may still wish to keep client satisfaction levels high byensuring that a high proportion of requests for on-demand instances arefulfilled (i.e., the operator may wish to ensure that at most a verysmall fraction of requests for on-demand instances are turned downbecause insufficient resource instances are available). In theembodiment illustrated in FIG. 16, the resource manager 180 may maintaina buffer of instances in the available instance pool 1625 specificallyto meet current and/or anticipated on-demand instance requests. In someembodiments, the resource manager 180 may be required to respond to aninstance acquisition request for an on-demand instance within a veryshort response time window, which may necessitate that the instances insuch a buffer have the interruptible-without-notification setting. Thus,in such embodiments, the total number ofinterruptible-without-notification instances (either in the availableinstance pool or in the in-use interruptible instance pools) may bebased on the number of unfulfilled reservation slots 1621, the projecteddemand for reserved instances, and/or on the size of the on-demandbuffer to be maintained by the resource manager 180. In someenvironments separate pools or sub-pools may be maintained to respond tofulfillment requests and to respond to on-demand instance requests. Inone embodiment separate in-use instance pools or sub-pools may bemaintained for different supported interruptibility levels.

The resource manager 180 may support one or more enhancedinterruptibility settings, in addition to the baseline or defaultinterruptible-without-notification setting, in some embodiments. Asnoted above, depending on the specifics of their applications, someclients 148 may be interested in acquiring instances that, while stilleconomical compared to reserved instances or on-demand instances, haveinterruptibility settings that allow the clients to save the state ofthe applications and/or complete some critical work before the instancesare interrupted or stopped. For example, in one embodiment, the resourcemanager 180 may support an interruptibility setting that gives a clienta five-minute advance warning before access to an instance is revoked.Multiple enhanced interruptibility settings may be implemented in someembodiments, e.g., a five-minute-warning setting and athirty-minute-warning setting. The pricing for instances with differentenhanced interruptibility settings may vary over time, e.g., in responseto supply and demand for the various levels of interruptibilitysupported. In some implementations, instead of or in addition tosupporting one or more interruptibility settings with fixed, discretewarning periods (e.g., five minutes or thirty minutes), the resourcemanager 180 may support a variable warning period based on price. Forexample, the length of the warning period provided may vary at thegranularity of a minute based on the price the client is willing topay—clients willing to pay one amount may get a ten minute warning,while clients willing to pay slightly more may get eleven minutewarnings, and so on. The various enhanced interruptibility settings thatsupport advance warnings may be termed “interruptible-with-notification”settings or “interruptible-with-advance-warning” settings herein.Pricing rates for the interruptible-without-notification andinterruptible-with-notification instances may be termed “interruptibleinstance pricing rates” and “enhanced-interruptibility instance pricingrates” respectively herein. One or more sub-pools of the availableinstance pool may be maintained to respond to enhanced-interruptibilityinstance requests; such pools may be termed “enhanced-interruptibilitysub-pools” herein. In some implementations, the currentenhanced-interruptibility instance pricing rate may depend on thecurrent size of the enhanced-interruptibility sub-pool(s), while thecurrent interruptible instance pricing rate may depend on the total sizeof the available instance pool 1625.

The pricing rates for instances with each of the different levels ofinterruptibility supported may be based at least in part on the expectedrate of requests for the respective interruptibility levels in someembodiments, and/or the expected rate of interruptibility upgraderequests. The resource manager 180 may monitor request rates for thedifferent types of instances and develop models or projections of futurerequest rates to help in determining the various pricing rates. In someembodiments the pricing optimizer 181 may perform some of theestimations and/or projections used for pricing differentinterruptibility levels, e.g., based on usage records and requestrecords gathered by metrics agents. An interface manager 182 may beresponsible for implementing functionality related to variousprogrammatic interfaces supporting interactions with the resourcemanager 180 and/or pricing optimizer 181 in some embodiments.

In order to meet demand for enhanced interruptibility instances, asnoted above, the resource manager 180 may set aside a dynamically sizedsubset of the available instance pool 1625 as one or moreenhanced-interruptibility sub-pools 1617. Instances may be moved in andout of the sub-pool or sub-pools, e.g., either to the in-use instancespool 1601, or to the interruptible-without-notification portion of theavailable instances pool 1625, based on current and/or projected supplyand demand, and the relative pricing of enhanced-interruptibilityinstances may vary based on supply and demand as well. For example, ifthe rate of requests for enhanced-interruptibility instances increases,in some embodiments the price and/or number of instances in theenhanced-interruptibility sub-pools may be increased accordingly, aslong as the resource manager 180 is still able to maintain the reservesneeded for outstanding reservations and the buffer for expectedon-demand instance request rates. An enhanced-interruptibility sub-poolmay be termed a “convertible” sub-pool in some embodiments, indicatingthat instances in the sub-pool may have their interruptibility settingsconverted or upgraded from interruptible-without-notification to someother level, e.g., based on demand and price.

The resource manager 180 may thus have to balance a number ofpotentially competing demands when deciding how to size the variouspools and sub-pools in some embodiments—e.g., the commitments made toclients that have unfulfilled reservations, the goal of respondingaffirmatively to the vast majority of requests for on-demand instances,and the goal of increasing revenue and utilization by providingotherwise idle resources to clients that have applications that can beinterrupted with or without warning periods. In some cases the sameclient 148 may wish to utilize different types of pricing models and/orinterruptibility settings for different subsets of the client'sapplication set—e.g., such a client may use any combination of reservedinstances, on-demand instances, interruptible-without-notificationinstances, as well as enhanced-interruptibility instances. If the clientopts in to receive recommendations from the pricing optimizer 181, thepricing optimizer may generate recommendations that include actions tobe taken with respect to the respective number of instances withdifferent levels of interruptibility that the client should acquire ordiscard, as well as the kinds of recommended actions described earlier.Recommended actions for instances with different interruptibility levelsmay be automated for those clients that opt in for such an automationservice in one embodiment.

In some embodiments, the resource manager 180 may also support upgradesand/or downgrades of the interruptibility settings of an instanceallocated to a client 148. E.g., a client 148 may be willing to pay abaseline pricing rate for a given instance for a period of time duringwhich the instance had an interruptible-without-notification setting,and may be interested in upgrading the instance to aninterruptible-with-notification setting for an additional price for someperiod of time. Interruptibility downgrades, e.g., from aninterruptible-with-thirty-minute-warning setting to aninterruptible-with-five-minute-warning setting, may also be supported insome embodiments, potentially with a corresponding reduction in price.In general, in several embodiments, the billing amount charged to aclient may be based at least in part on (a) the pricing rates in effectfor the different levels of interruptibility of an instance while it wasallocated to the client and (b) the respective durations for which theinstance's interruptibility was set to each of the levels. For example,if a client 148 used an instance 130 at interruptibility level I1 for atime period T1 during which the instance pricing for level I1 was P1,and the client used that same instance at interruptibility level I2 fora time period T2 during which the instance pricing for level I2 was P2,the billing amounts charged to the client for that instance may be basedat least in part on the sum of the products (T1*P1)+(T2*P2).

Example Web Interfaces for Interruptibility Related Requests

FIG. 17 illustrates a portion of an example web-based interface that maybe implemented to support multiple instance interruptibility levels,according to some embodiments. In the illustrated embodiment, a web 1700may include a message area 1703 indicating that recent pricing historyfor several different levels of interruptibility is being displayed.Filtering options 1705 may allow a client to select or specify thetypes, availability zones, and/or other characteristics of the instancesfor which pricing data is to be displayed. For example, the client maywish to see the pricing history for large instances within one or moreavailability zones that are convenient to the client. Drop-down menusmay be provided in some implementations to limit the set of filteringchoices that the client may make to only those options that are relevantto that particular client.

A graphical region 1711 may display the price fluctuations for thedifferent levels of instance interruptibility that are supported. In theexample, shown, four different pricing trends are displayed: “no-delay”,“5-minute-delay”, “30-minute-delay” and “60-minute-delay”. The no-delayline may correspond to the interruptible-without-notification settingdiscussed above. The 5-minute, 30-minute and 60-minute delay lines mayrepresent different warning period durations between the time that anaccess revocation notification transmitted by the resource manager 180is received by a client 148 for an allocated instance, and the time thataccess to that instance is revoked by the resource manager 180. As notedabove, the resource manager 180 may send an access revocationnotification to a client with an allocated instance for a number ofdifferent reasons in various embodiments, e.g., in response to afulfillment request for a reservation, if a higher bid than the pricecurrently being charged for the instance is received, in response toanticipated requests for on-demand or reserved instances, and so on. Insome embodiments, pricing for non-interruptible instances (e.g.,on-demand instances that are obtained for a specified period duringwhich access cannot be interrupted by the resource manager 180) may alsobe shown for comparison. In some implementations the web page 1700 mayinclude one or more fields (such as fields 1714) allowing the client tosubmit a request to acquire one or more instances with desiredinterruptibility settings. A “continue” button 1723 may be used by theclient to proceed to additional steps involved in acquiring theinstances specified, e.g., to a request verification step.

FIG. 18 illustrates a portion of an example web-based interface that maybe implemented to support upgrades between instance interruptibilitylevels, according to some embodiments. As shown, a web-page 1800 mayinclude a message region 1803 indicating that a list of instances forwhich interruptibility upgrades and/or downgrades are supported, andwhich are currently allocated to the client 148, is displayed on thepage. A list region 1807 may display details of the various instancesfor which upgrades/downgrades are possible, such as the currentinterruptibility settings of the instances, and/or the costs of each ofthe possible interruptibility modifications. In some implementations theclient may be allowed to request desired upgrades or downgrades fromwithin the interface, e.g., via the buttons labeled “Upgrade” or“Downgrade” in FIG. 18. In the illustrated example, one of the optionsbeing provided is to change an instance's interruptibility setting to“not-interruptible”, which may have the effect of converting a currentlyinterruptible instance to the equivalent of an on-demand instance. Inaddition to, or instead of, web-based interfaces such as those shown inFIGS. 17 and 18, other types of programmatic interfaces for supplyinginterruptibility-related information, and receiving and responding torequests regarding interruptibility levels may be provided in somecases. For example, one or more APIs, installable client programs thatare not web-based, and/or command-line tools may be implemented invarious embodiments.

Methods for Supporting Enhanced Interruptibility Levels

FIG. 19 is a flow diagram illustrating aspects of the operation of aresource manager 180 configured to support multiple instanceinterruptibility levels, according to at least one embodiment. In theillustrated embodiment, the resource manager 180 may provide pricinginformation for each of a plurality of different instanceinterruptibility levels, e.g., via a programmatic interface similar tothe types of web pages shown in FIG. 17. Clients 148 may includespecifications of desired interruptibility settings in their instanceacquisition requests. When the resource manager 180 receives a requestspecifying a desired interruptibility level (element 1905), an instancewith the requested interruptibility setting may be allocated to theclient (element 1913). In some embodiments the resource manager 180 maymaintain multiple pools or sub-pools of instances to satisfy demand forrespective interruptibility settings. In other embodiments, a singlepool of available instances may be maintained, and the interruptibilitysetting of a selected available instance may be set to the desired levelwhen the instance is allocated to a requesting client. In someimplementations separate pools of in-use instances may be maintained foreach supported interruptibility setting, e.g., in addition to the typesof in-use pools shown in FIG. 16.

The billing rates charged to a client may be based at least in part onthe pricing rates of the interruptibility settings used by the client,and the durations for which the interruptibility settings applied to theclient's allocated instances. For example, one client C1 may be billedat a pricing rate P1 for using a resource instance R1 for time T1 withinterruptibility setting I1. Another client C2, who may use a resourceinstance R2 with the same performance capabilities as R1 and for thesame length of time T1, may be billed at a different pricing rate P2 ifC2 requested a different interruptibility setting I2. The resourcemanager 180 may determine the billing amounts to be charged to theclient 148 based on the applicable interruptibility settings andinterruptibility setting durations, as shown in element 1915 of FIG. 19,and notify the client regarding the billing amounts (element 1917).

FIG. 20 is a flow diagram illustrating aspects of the operation of aresource manager 180 configured to support upgrades betweeninterruptibility levels, according to at least one embodiment. In theillustrated embodiment, when the resource manager receives an instanceacquisition request from a client (element 2001), an instance with adefault interruptibility setting such as theinterruptible-without-notification setting may be allocated to therequester (element 2005), e.g., if no interruptibility setting isspecified in the request. If an interruptibility setting is specified inthe instance acquisition request, an instance with that setting may beallocated instead. Subsequent to the allocation, if the resource managerreceives an interruptibility upgrade request (element 2009), theresource manager may determine whether to accept the upgrade requestbased on one or more factors such as for example the current size of anavailable instance pool 1625, a current size of one or moreenhanced-interruptibility sub-pools 1617, the price the requestingclient is willing to pay for the upgrade, and so on.

If the resource manager determines that the upgrade request isacceptable (element 2013), the interruptibility setting of the instancein question may be modified as requested (element 2017). If the upgraderequest is found unacceptable, it may be rejected (element 2029). Ineither case, billing amount(s) based at least in part on theinterruptibility setting or settings in effect during the time theresource instance was allocated to the client 148 may be determined(element 2021) and the client 148 may be notified of the various billingamounts incurred (element 2025). In some implementations where forexample multiple interruptibility settings are supported, if a client148 sends an upgrade request with a specified bid for a desired targetinterruptibility setting, and the resource manager 180 determines thatthe request is unacceptable, the resource manager 180 may attempt tofind another interruptibility setting for which the bid is acceptable.If such an alternative setting is found, the client may be notified. Forexample, the client may bid SD for an upgrade from interruptibilitylevel I1 to level I3. If the resource manager finds that SD isinsufficient to enhance the interruptibility from level I1 to level 13,but is acceptable to enhance the interruptibility level from I1 to levelI2, the resource manager 180 may inform the client that level I2 isacceptable, and may set the interruptibility level of the instance to I2if the client agrees. In some embodiments, the client 148 may be able torequest that the resource manager 180 select the best possibleinterruptibility level for a specified price that the client is willingto pay, and the resource manager may determine the specificinterruptibility setting (or the length of the advance warning foraccess revocation) to be used for the client's instance.

As noted earlier, the resource manager may be responsible for populatingand resizing the various instance pools of a provider network in someembodiments. FIG. 21 is a flow diagram illustrating aspects of theoperation of a resource manager configured to assign instances to anavailable instance pool and at least one enhanced-interruptibilitysub-pool, according to at least one embodiment. The resource manager 180may assign one or more currently idle instances to an available instancepool 1625, as shown in element 2101, and select a subset of thoseavailable instances for inclusion in an enhanced interruptibilitysub-pool or sub-pools (element 2105). Multiple sub-pools may bemaintained in some embodiments where multiple levels of enhancedinterruptibility are supported. Various types of events may lead toresizing of one or more of the pools in different embodiments. Forexample, the resource manager may wait for the next relevant instanceevent (element 2109), such as an in-use instance being deactivated,released or freed, new instances being installed at a data center by theoperator of the provider network, or new instance acquisition requestsarriving. If the supply of available instances increases, e.g., as aresult of an instance being released or more instances being broughtonline, the size of the available pool 1625 may be increased (element2113). Depending on the current and/or anticipated demand and price forenhanced interruptibility instances, some or all of the newly availableinstances may be included within the enhanced interruptibility sub-pools1617. If the supply of available instances decreases, e.g. as a resultof an approved instance acquisition request, the sizes of the relevantpool and/or sub-pool may decrease (element 2117). In either case, theprices associated with the different interruptibility settings andupgrades may also be modified dynamically as the pool sizes change. Thespecific actions taken by the resource manager 180 in response to eventsof various types may differ from implementation to implementation. Forexample, in response to an increased demand forenhanced-interruptibility instances, whether the resource manager 180increases an enhanced-interruptibility sub-pool size while keeping theenhanced-interruptibility pricing fixed, or whether the sub-pool size iskept fixed while the price is raised, or whether both the size and theprice are raised, may vary based on the specific algorithms orheuristics being used by the resource manager I differentimplementations.

Various instance pool sizes may also be changed as a result of otherfactors in addition to the types of events mentioned above (such asinstances being freed or allocated) in some embodiments. FIG. 22 is aflow diagram illustrating aspects of the operation of a resource manager180 configured to resize instance pools based at least on part on usagetrends for on-reserved instances and on-demand instances, according toat least one embodiment. The resource manager 180 may gather metrics onthe variations in the number of active or allocated reserved instancesand/or on-demand instances over time (element 2201). Based on themetrics, the resource manager 180 may identify usage trends and developprojections for expected future usage of the different types ofinstances. Projections may be developed for varying future time periodsin some embodiments. For example, by examining hour-by-hour usage datafor on-demand instances over a period of a few months, the resourcemanager 180 may be able to project that the number of on-demand instanceacquisition requests typically rises by X % between 6 am and 8 am onMondays. Accordingly, the resource manager may ensure that sufficientavailable interruptible-without-notification instances are set aside tomeet the X % increase—e.g., by reducing the number ofenhanced-interruptibility instances at the appropriate times.Longer-term trends may also be identified on the basis of past usage insome embodiments—e.g., the resource manager 180 may be able to predictthat the total number of reserved instances is going to rise by 30% overthe next three months, and/or that the fraction of reserved instanceslots that are unused at any given time is likely to rise by 20% overthe next three months.

Based at least in part on such short-term and/or longer-termprojections, the resource manager 180 may make a determination as towhether any of the instance pools or sub-pools, such as theenhanced-interruptibility sub-pools, need to be resized (element 2209).If the resource manager 180 determines that one or more pools orsub-pools should be resized, it may determine when such resizing shouldbe performed, and move instances in or out of the appropriate poolsaccordingly (element 2213). If no changes to current pool sizes areneeded, the resource manager may resume monitoring the usage of varioustypes of resources and make new projections as needed, e.g., repeatingthe steps illustrated in elements 2201, 2205 and 2209. In someembodiments projections of future needs for various types of instancesmay be made based on a predetermined schedule. In other embodimentsprojections may be developed in response to threshold conditions—e.g.,if the number of available instances falls to less than 10% of the totalinstances in an availability zone, an analysis of past usage trends andcorresponding future projections may be initiated. In addition tochanging the sizes of various pools and sub-pools, the pricing ratesassociated with different interruptibility settings may also be adjustedbased on trend analysis in some embodiments. For example, in oneembodiment usage trends may predict a rise in demand forenhanced-interruptibility instances by a web retailing client during aforthcoming retail sales period, and the resource manager 180 may raiseprices for enhanced interruptibility instances based on the prediction.

Dynamic Pricing for Flexible-Granularity Execution of Stateful ClientApplications

Excess resource capacity of a provider resource may be reserved andallocated in units of resource instances in many of the embodimentsdescribed above. In some embodiments and for certain kinds of clientapplications, it may be beneficial to manage and schedule resources atother granularities in addition to, or instead of, entire resourceinstances. FIG. 23 illustrates a system 2300 in which the resourcemanager 180 is configurable to determine a dynamically varying price perexecution unit (expressed for example in units such as CPU-seconds,CPU-minutes, CPU-hours, MegaFLOPs, Megahertz, Gigahertz and the like) ofexcess resource capacity, and use the price to select client-providedapplications for execution, according to at least some embodiments. Aclient 148 may provide one or more application packages to the resourcemanager 180, e.g., with the help of a programmatic interface such as anAPI or a one or more web pages implemented by interface manager 182,where each application package includes an executable object and has anassociated pricing constraint to be used to schedule the execution ofthe executable object. For example, a client may provide an executableobject that can be deployed and run on a JVM that is compliant with aspecified version of the Java™ Development Kit (JDK), a platform thatsupports various interpreted or compiled programming languages such asRuby, Python, Perl, C, C++ and the like, or on a high-performancecomputing execution platform that conforms to one or more industrystandards. The client 148 may indicate, as a pricing constraint, that itis willing to pay up to specified amount for each CPU-minute that theexecutable is run on an execution platform with a specified performancecapacity (e.g., on a JDK 1.6 JVM running on CPU X at 3 GHz or higherclock rate). The application packages provided by clients may be storedin an application repository 2390 in some embodiments. Various otherdetails regarding the application may also be specified by the clientvia the application package, such as input/output needs of theapplication; further details of application package contents areprovided below.

In the illustrated embodiment, a subset of available instances (such asinstances 130L, 130M, 130N and 130O) may be assigned to a “soaker” pool2317 at a given point in time, representing a pool of excess resourcecapacity that is usable for the application packages. The resourcemanager 180 may instantiate a number of execution platforms (EPs) 2305on the instances 130 of the soaker pool, as needed, to satisfy theexecution requests for the application packages provided by the clients.For example, an EP 2305A may be instantiated on instance 130L, two EPs2305B and 2305C may be instantiated on instance 130M, and one EP 2305Dmay span multiple instances such as 130N and 130O. An execution platformmay comprise any of a variety of middleware entities or softwarecollections that may be needed for execution of client applications,such as for example JVMs, application server instances, databaseinstances, special-purpose or general-purpose operating systems,high-performance computing platforms such as genome analysis platforms,simulation test beds, map-reduce execution environments, and the like.

A flexible mapping of execution platforms to the excess resourcecapacity of a provider network may be implemented in someembodiments—e.g., a single EP 2305 may be instantiated on one resourceinstance 130, or multiple EPs 2305 may be instantiated on one resourceinstance 130, or a single EP 2305 may be instantiated on multipleresource instances 130. In some embodiments where for example a resourceinstance 130 typically comprises a virtual compute platform that relieson a hypervisor running on some “bare-metal” hardware asset, some of thebare-metal hardware assets may be used for the soaker pool 2317 withoutinstantiating hypervisors or other components typically used forresource instances. Pricing per execution unit (e.g., per CPU-minute)for different types of EPs may vary dynamically in some embodiments,based on factors such as the supply and demand for such EPs, theperformance capabilities of the EPs, the requirements of the resourcemanager to maintain available instances to support unfulfilledreservation slots, and so on.

The resource manager 180 may attempt to find a “best match” executionplatform for various application packages using one or more criteria.For example, in one embodiment, the resource manager 180 may select aparticular EP 2305 on which to schedule execution of the executableobject of an application package based at least in part on the currentpricing of execution units of the EP 2305 and the pricing constraints ofthe application package (e.g., the maximum price the client is willingto pay). If a match is found, execution of the client's application maybe started (or resumed) on the selected EP 2305.

Any of a number of events or conditions may result in the executionbeing suspended or stopped in some embodiments. For example, in oneembodiment, in response to a price-based interruption event such as thereceipt of a new application package for which the corresponding clientis willing to pay a higher price than is currently being charged, arepresentation of the current state of the application may be saved, andthe execution of the executable object may be stopped on the EP 2305.Another example price-based interruption event may comprise thedetermination by resource manager 180 that a different EP 2305 hasbecome available that may be better suited for the application, e.g.,because of a lower price or because the different EP 2305 supportsadditional functionality or capabilities than the EP currently beingused. The resource manager 180 may try to schedule further execution ofa stopped/suspended application on other EPs based for example onavailability and pricing.

In some embodiments, a client 148 may provide an application package tothe resource manager 180 and ask for a quote for completing execution ofthe application. The resource manager may analyze the applicationpackage in response to the quote request, and may determine and providea quote responsive to the request, taking into account various factorssuch as the current and/or expected future pricing of EPs 2305appropriate for the client's application. The client 148 may receive thequote and indicate a bid responsive to the quote, e.g., as part ofpricing constraint information provided with the application package.The resource manager 180 may respond to the bid affirmatively, byscheduling execution of the client's application on a suitable EP, or,if the bid is found to be insufficient, the resource manager 180 mayreject the bid at least temporarily. A client 148 may ask for bid tocomplete execution of an application after a portion of the applicationhas already been executed in some embodiments. For example, if anapplication is run for a while and then stopped as a result of aprice-based interruption event, the client may submit a quote request tothe resource manager to obtain an estimate of how much it might cost tocomplete the remaining portion of the application execution. In someimplementations, if a bid responsive to a quote is initially rejected,that same bid may later be found acceptable as a result of price changesthat have occurred since the initial rejection; thus, the execution ofan application may be scheduled if and when the bid becomes acceptable.

Example Application Package Contents

FIG. 24 illustrates example contents of an application package that maybe submitted by a client 148 to a resource manager 180, according to atleast some embodiments. The application package (AP) 2405A may comprisean executable object 2410, such as a jar (Java™ archive) file, a war(web application archive) file, an ear (enterprise archive) file, an exefile, one or more scripts written in any appropriate language such asPython, Ruby, Perl, any of various variants of SQL, shell scripts, andthe like. In one implementation supporting parallel or multi-threadedapplication types, the executable object 2410 may comprise one thread,or a few threads, of a multi-threaded or parallel application—e.g.,several application packages 2405 may be created for a singlemulti-threaded application, such that each package 2405 specifies asubset of the complete set of threads of the application as thepackage's executable object 2410. In some embodiments the AP 2405A mayinclude a set of preferred or required resource specifications 2415,such as a minimum CPU speed, CPU vendor or architecture details, minimummain memory requirements, an operating system version, applicationserver version, database management system vendor and version, and soon. Some of the resource specifications may be labeled as mandatory,i.e., the resource manager 180 may be unable to execute the applicationif the mandatory requirements are not met. Non-mandatory resourcespecifications may serve as hints or advisories to the resource manager;e.g., the resource manager may in some implementations make a besteffort to find execution platforms that meet non-mandatoryspecifications.

Some types of applications may have dependencies or constraints—forexample, one application may rely on an external web site beingavailable, or may perform better when an external web site is available.Another application may be configured to obtain work tasks or jobs froman external job queue, such that if the job queue is empty orunreachable the application may not be able to perform much useful work.An AP 2405A may contain indications of such execution constraints 2420in some implementations. A client 148 may include pricing constraints2425 in the application package itself in some embodiments—e.g., themaximum price the client is willing to pay per CPU-minute or per someother execution unit. In some implementations the client may specifypricing constraints for completing execution of the application, insteadof or in addition to specifying the client's bid per execution unit.Pricing constraints associated with an application package may bespecified and/or stored separately from other contents of theapplication package in some embodiments, e.g., an application packagemay not include the pricing constraints in some cases. A client 148 mayin some implementations update the bid or other details of the pricingconstraints 2425 as needed during the lifetime of the application—e.g.,if an application is suspended or stopped because the prevailing pricefor using the application platform it needs has risen beyond the pricebid by the client originally, the client may be allowed to raise thebid; and if the client wishes to lower costs for some reasons, theclient may be allowed to lower the bid for one or more of the client'sapplication packages.

When resource manager 180 received an application package 2405, in someembodiments it may store the package in a persistent applicationrepository 2390. If a suitable execution platform 2305 can be found forthe application submitted by the client, the execution of theapplication on that selected EP 2305 may be initiated. In someimplementations the application package 2405 may only be stored if an EP2305 cannot immediately be found for it, i.e., an application package2405 may be stored in the application repository 2390 only when and ifthe execution of the application cannot proceed. In some embodiments,the resource manager 180 may also store a persistent application stateobject (ASO) 2429 (such as a serialized Java™ object file, or any otherobject representation of the state of an application that allows theresumption of the application when a suitable execution platform becomeavailable) for each application object 2405—e.g., ASO 2429B forapplication package 2405B, ASO 2429C for application package 2405C, andso on. For applications whose execution has not yet begun, the staterepresentation object 2429 may be empty. Other information not shown inFIG. 24 may be included in application packages 2405 and/or inapplication repository 2390 in some embodiments, such as for example oneor more representation of execution metrics (e.g., how many CPU-minutesof execution have been completed so far for the application), executionhistory (on which specific execution platforms the application has beenexecuted), and the like. In some embodiments security constraints mayalso be associated with each application package 2405—e.g., the client148 may encrypt portions of the application package and/or use a digitalsignature on portions of the application package. In such cases theresource manager 180 and the client 148 may need to transfer or exchangeone or more keys to implement the security mechanism being used.

Quote-Based Pricing for Application Execution

FIG. 25 illustrates example interactions between a client 148 and aresource manager 180 configured to provide quotes for completingexecution of an application, according to at least some embodiments. Asindicated by the arrow labeled “1”, a client 148 may transmit or submita quote request for an application package 2405 to the resource manager180. The resource manager may in some embodiments implement aprogrammatic interface (e.g., via a web site or an API) for thesubmission of quote request and/or application packages, and the clientmay use the interface for the quote request. In some implementations aquote request may be included within an application package 2405, or maybe transmitted together with an application package 2405

When the resource manager receives the quote request, it may analyze thecontents of the corresponding AP 2405. In some embodiments, as shown bythe arrow labeled “2” in FIG. 25, the resource manager 180 may send anoptional request to the pricing optimizer 181 to help analyze the AP2405. In embodiments where quote requests may be submitted forapplications that have already completed a portion of their execution,the resource manager 180 and/or the pricing optimizer 181 may examinethe application state object (ASO) 2429 as well as elements of the AP2405 (such as resource specifications 2415) to help estimate theremaining resource requirements for the application. In addition toexamining the AP 2405 and/or the ASO, the resource manager 180 and/orthe pricing optimizer 181 may obtain pricing history for executionplatforms 2305 of the type needed by the application, and may use anycombination of these data sources to determine a quote for completingexecution of the application. In embodiments where the pricing optimizer181 is involved in AP analysis, the pricing optimizer 181 may send ananalysis response to the resource manager 180, as indicated by the arrowlabeled “3” in FIG. 25.

The quote may include a fixed price that the client would be billed forcompleting the execution of the application in some embodiments. In oneimplementation, several alternate quotes may be provided, each with anassociated time period for completing the application execution—e.g.,one quote for completing the application within a week, another quotefor completing the application within two weeks, and so on. In anotherimplementation, the resource manager 180 may provide several alternatequotes for completing different fractions of execution (or differentnumbers of total client transactions, in the case of transactionalworkloads)—e.g., the resource manager 180 may provide a first quote forcompleting 50 simulation runs, another quote for 100 simulation runs,and so on. When the quote or set of quotes is determined, either by theresource manager 180 alone or as a result of cooperation between theresource manager 180 and the pricing optimizer 181, the quote may beprovided to the client 148, as indicated by the arrow labeled “4” inFIG. 25. In response to the quote or quotes, the client 148 may submit abid, as indicated by the arrow labeled “5”. If the bid is acceptable,the resource manager 180 may schedule the execution of the client'sapplication if a suitable EP 2305 is available. If no appropriate EP iscurrently available, or if the bid is too low, the client's applicationpackage may be stored in application repository 2390 for laterexecution.

Methods for Pricing and Scheduling Client-Provided Applications onExecution Platforms

FIG. 26 is a flow diagram illustrating aspects of the operation of aresource manager 180 configured to schedule execution of client-providedapplications on execution platforms 2305 with dynamically changingpricing per unit of execution, according to at least some embodiments.As shown in element 2601, the resource manager 180 may determine thenext application package 2405 for which it is to attempt executionscheduling. An application package 2405 that has just been submitted bya client 148 may be the next one to be scheduled, or, if there are oneor more application packages 2405 in the application repository 2390whose executables are currently not running, an application packagesfrom the repository may be the next one to be scheduled. The resourcemanager 180 may in some implementations maintain a queue or list ofschedulable applications, ranked based on the basis of one or morepriority criteria such as the bid value associated with each applicationpackage 2405, and may pick the highest priority application package fromsuch a queue or list for consideration as the next application packageto be scheduled. In some implementations, multiple such queues or listsmay be maintained, e.g., different queues may be maintained fordifferent sizes and/or other characteristics of supported executionplatforms. One queue may be maintained for EPs 2305 that comprise JVMs,another queue for Python execution platforms, and so on, for example.

The execution of the executable object 2410 of the application package2405 being considered may be scheduled on an available executionplatform 2305 that meets the requirements of the application (element2605 of FIG. 26). If multiple appropriate execution platforms areavailable, the resource manager 180 may select one from among them basedon one or more selection heuristics or algorithms, for example using aload balancing technique to spread the workload among availableexecution platforms, or an affinity technique that attempts to scheduleall of a given client's applications on the same set of executionplatforms. The resource manager may then wait for the execution of theclient's application to complete on the selected execution platform2305, or for a price-based interruption event to occur that may resultin the execution being suspended or stopped (element 2607).

If a price-based interruption event occurs (as determined in element2609), e.g., if a new application package arrives with a higher bid forthe type of execution platform being used currently for the client'sapplication, the resource manager may save the application state andstop/suspend the execution of the executable 2410 (element 2613). Theapplication state may be saved in the application repository 2390 insome implementations, e.g., in the form of a persistent applicationstate object 2429 that contains enough information to resume theapplication's execution at the point it was stopped. If the executioncompletes (i.e., if the next event that influences the execution of theclient's application is not a price-based interruption), as alsodetermined in element 2609, the resource manager may continue on toidentify the next application package to schedule. In someimplementations the application package may be removed from theapplication repository 2390 upon completion of the application'sexecution.

If a price-based interruption led to the stoppage/suspension of theclient's application on the selected execution platform 2305, as shownin element 2617 the resource manager 180 may allocate that executionplatform 2305 to a different client-provided application (e.g., a clientapplication for which a higher bid was received), if such an applicationis found. In some cases the interruption may lead to the resourcemanager making one or more pricing changes, e.g., raising an advertisedminimum price for the use of execution platforms 2305 (element 2620).The interruption event may also result in a change to the size of thesoaker pool in some cases—e.g., the interruption event may comprise thecompletion of the execution of some other application, or the bring-upof additional hardware at a data center, either of which may result in amore economical execution platform becoming available. In some cases,the price-based interrupt may result in the client's application beingsuspended for a while, while in other cases, a new target executionplatform that meets the client's pricing constraints may be foundimmediately and the client's application may begin execution on thenewly found target platform very quickly. The resource manager mayresume its functionality after the price-based interrupt has beenhandled—e.g., it may attempt to determine the next application packageto schedule (which may or may not be the application package whoseexecutable has just been suspended in some cases, depending on thecriteria being used to select the next package to schedule). It is notedthat various aspects of the functionality illustrated in FIG. 26 may beperformed in parallel, or in a different order than shown in FIG. 26, insome implementations. For example, the resource manager may comprisemultiple threads that run in parallel to schedule client applications asquickly as possible.

FIG. 27 is a flow diagram illustrating aspects of the operation of aresource manager 180 configured to provide quotes for completingexecution of an application, according to at least some embodiments. Aquote request may be received (element 2701) for an application package2405 from a client 148, either accompanying the initial submission ofthe application package, or at some later point during the lifecycle ofthe application package. In some implementations quote requests may evenbe submitted for a currently-running application, while in otherimplementations the resource manager 180 may only accept quote requestsfor applications that are currently not running. In response to quoterequest, the resource manager 180 may analyze the application packageand/or the current state of the application (e.g., the staterepresentation saved in the corresponding persistent application stateobject 2429), as shown in element 2705 of FIG. 27. In some embodiments,as shown in FIG. 25, the pricing optimizer may also be used to analyzethe application package and/or state.

Based at least in part on results of the analysis, and at least in parton the current price associated with execution units (such asCPU-minutes or CPU-hours) of the execution units usable for theapplication, a quote for completing the execution of the application maybe determined (element 2709 of FIG. 27). The quote may then be providedto the requesting client 148 (element 2713). In some implementationsmultiple quotes may be provided—e.g., quotes for different totalcompletion times, or quotes for completing different workload amounts.The client may use the quote or quotes to make a new bid for theapplication package, e.g., by providing or updating a bid in the pricingconstraints section 2425 of the application package. The resourcemanager may accept or (at least temporarily) reject the bid asappropriate based on current conditions and/or pricing trends.

Example Web-Based Interface for Application Package Specifications

FIG. 28 illustrates a portion of an example web-based interface that maybe implemented to allow clients 148 to provide applicationspecifications to be used to schedule the client applications onexecution platforms, according to some embodiments. As shown, web page2800 of FIG. 28 may include a welcome message section 2803 that includesan instruction to the client to fill out as many details of the client'sapplication as possible using the form fields available on the page. Insome implementations links to additional information about the workingof the soaker pool, such as details about the different types andperformance capabilities of execution platforms, may also be provided,e.g., via button 2807.

A number of fields 2809 may be implemented for the client 148 to provideapplication details to the resource manager 180 in the illustratedembodiment. For example, the resource manager 180 may implement adrop-down menu allowing the client to select from among one or moresupported executable types (e.g., Java™ executables, Ruby scripts,Python scripts, Perl scripts, and the like). In some implementationsinput and output modes for the application may be specified—e.g., if theexecutable object of the application relies on input parameters or inputdata, the source of such input may be specified, and the target to whichany output produced by the executable may be specified. In theillustrated example, a default setting of an extensible markup language(XML) file has chosen for input, and a test file has been specified forapplication output. In some embodiments some of the output generated bythe client's executable may be stored in a different location orcontainer than the execution platform being used for theexecutable—e.g., at least some of the output could be stored on anexternal storage instance or storage device, e.g., anindependently-managed device accessible via a network connection fromthe execution platform. Similarly, in some scenarios input for theexecutable may also be retrieved from external locations or containers.Clients may also be able to specify requirements for input/output fromor to external entities using interfaces similar to those shown in FIG.28 in some embodiments.

If the client's application requires CPUs with a minimum processingpower, and/or a minimum amount of main memory, such requirements mayalso be specified via web page 2800 in some implementations. Commandsthat the resource manager 180 may use to save application state (e.g., ashell script supplied by the client) may also be indicated in fields2809. If the application has special parallelism requirements, e.g., ifmultiple processors are needed, the parallelism specifications may alsobe provided using the interface.

In the example implementation showed in FIG. 28, pricing-relatedpreferences may also be specified by the client via form fields section2809. For example, the client may request a bid for the applicationusing one of the form fields. If quotes for complete execution are notrequested, the execution units (e.g., CPU-minutes or CPU-hours for theequivalent of a specified processor type and speed, labeled processor“PPP” in the example) to be used for bidding may be selectable by theclient 148 via another drop-down menu or form field. In someimplementations a bid, either per execution-unit or for completeexecution of the application, may also be provided by the client usingthe web interface. In addition to or instead of the web page 2800 shownin FIG. 28, other programmatic interfaces such as APIs or command lineinterfaces may be implemented in some embodiments for variousinteractions between the clients and the resource manager related topricing and scheduling application execution. Examples of suchinteractions supported by the programmatic interfaces in variousembodiments may include uploading application packages, submittingbid/quote requests, receiving bid/quote responses, control requests suchas stopping/starting application executables, requests for status (ofapplications, quotes or bids), cancelation requests (for applicationpackages, bids, or quotes), and modification requests (for applicationpackages, bids, or quotes).

In some embodiments clients 148 may also be provided the ability to optin to receive recommendations for their applications from the pricingoptimizer 181, similar in principle to the kinds of recommendationsdescribed earlier in conjunction with the description of FIG. 3. Thepricing optimizer may for example keep track of the usage of variousexecution platforms 2305 by a client's applications, and may be able toprovide recommendations on the kinds of execution platforms that theclient should bid for. Such recommendations may be especially helpful inembodiments where the pricing of execution platforms is tied to theperformance capabilities of the execution units, and clients may beunintentionally specifying inappropriate minimum performancerequirements or bidding for suboptimal execution platforms. The pricingoptimizer 181 may also analyze the impact or overhead of interruptionson the progress of a client's applications over time, and makerecommendations based on such analysis—e.g., if the overhead is high,the optimizer may recommend a higher bid, or a transition to moretraditional types of resource usage such as reserved instance use oron-demand instance use.

The resource manager 180 may in some embodiments implement multiplelevels of interruptibility for execution platforms 2305, similar to thetypes of instance interruptibility settings discussed in conjunctionwith the descriptions of FIGS. 16-18. The pricing of execution platforms2305 may be determined on the interruptibility setting requested by theclient in such embodiments. One or more sub-pools of the soaker pool2317 may be maintained to cater to different interruptibility settings.In such embodiments, the resource manager 180 may resize the sub-poolsand/or the soaker pool using techniques similar to those describedearlier for resizing the instance pools shown in FIG. 16.

Example Use Cases

The techniques described above for providing and implementingusage-based recommendations, supporting multiple levels ofinterruptibility, and scheduling and pricing execution ofclient-provided applications based on execution units other thaninstances, may be useful in a wide variety of environments. As the sizeand complexity of cloud-based resource provisioning grows, and more andmore applications are deployed into cloud environments, the probabilitythat resources of a particular type or in a particular data centerremain underutilized, while at the same time demand for that same typeof resource somewhere else is high, will also tend to grow. The abilityof a resource manager to match peaks in demand with currently idleresources will be useful in maintaining high customer satisfaction, andwill also help provider network operators to maximize their own returnon investment.

The functionality described above may also help to convince clients thatmay otherwise be reluctant to use cloud computing environments to tryout the services offered by provider networks with low risk. Forexample, a client may specify a fairly low budget limit to a pricingoptimizer, and allow the pricing optimizer to suggest recommendationsthat are within that budget limit. If the recommendations turn out to beuseful, the client may consider using the provider network for more orlarger applications. If the recommendations do not impress the client,the client may decide not to use the pricing optimizer (or even theprovider network as a whole), with few negative consequences. Theautomated implementation of recommendations made by the pricingoptimizer may allow those clients that are confident of the capabilitiesof the pricing optimizer to substantially reduce the overhead involvedin managing their cloud resource instances. The support for enhancedinterruptibility levels, and for dynamic pricing and execution ofclient-provided application executables, may significantly expand thedifferent types of applications that may be run economically using theprovider network's resources.

Illustrative Computing Device

In at least some embodiments, a server that implements a portion or allof one or more of the technologies described herein, including thetechniques to implement the functionality of pricing optimizer 181,resource manager 180, interface manager 182 and execution platforms 2305may include a general-purpose computer system that includes or isconfigured to access one or more computer-accessible media. FIG. 29illustrates such a general purpose computing device 3000. In theillustrated embodiment, computing device 3000 includes one or moreprocessors 3010 coupled to a system memory 3020 via an input/output(I/O) interface 3030. Computing device 3000 further includes a networkinterface 3040 coupled to I/O interface 3030.

In various embodiments, computing device 3000 may be a uniprocessorsystem including one processor 3010, or a multiprocessor systemincluding several processors 3010 (e.g., two, four, eight, or anothersuitable number). Processors 3010 may be any suitable processors capableof executing instructions. For example, in various embodiments,processors 3010 may be general-purpose or embedded processorsimplementing any of a variety of instruction set architectures (ISAs),such as the x86, PowerPC, SPARC, or MIPS ISAs, or any other suitableISA. In multiprocessor systems, each of processors 3010 may commonly,but not necessarily, implement the same ISA.

System memory 3020 may be configured to store instructions and dataaccessible by processor(s) 3010. In various embodiments, system memory3020 may be implemented using any suitable memory technology, such asstatic random access memory (SRAM), synchronous dynamic RAM (SDRAM),nonvolatile/Flash-type memory, or any other type of memory. In theillustrated embodiment, program instructions and data implementing oneor more desired functions, such as those methods, techniques, and datadescribed above, are shown stored within system memory 3020 as code 3025and data 3026.

In one embodiment, I/O interface 3030 may be configured to coordinateI/O traffic between processor 3010, system memory 3020, and anyperipheral devices in the device, including network interface 3040 orother peripheral interfaces. In some embodiments, I/O interface 3030 mayperform any necessary protocol, timing or other data transformations toconvert data signals from one component (e.g., system memory 3020) intoa format suitable for use by another component (e.g., processor 3010).In some embodiments, I/O interface 3030 may include support for devicesattached through various types of peripheral buses, such as a variant ofthe Peripheral Component Interconnect (PCI) bus standard or theUniversal Serial Bus (USB) standard, for example. In some embodiments,the function of I/O interface 3030 may be split into two or moreseparate components, such as a north bridge and a south bridge, forexample. Also, in some embodiments some or all of the functionality ofI/O interface 3030, such as an interface to system memory 3020, may beincorporated directly into processor 3010.

Network interface 3040 may be configured to allow data to be exchangedbetween computing device 3000 and other devices 3060 attached to anetwork or networks 3050, such as other computer systems or devices asillustrated in FIGS. 1 through 28, for example. In various embodiments,network interface 3040 may support communication via any suitable wiredor wireless general data networks, such as types of Ethernet network,for example. Additionally, network interface 3040 may supportcommunication via telecommunications/telephony networks such as analogvoice networks or digital fiber communications networks, via storagearea networks such as Fibre Channel SANs, or via any other suitable typeof network and/or protocol.

In some embodiments, system memory 3020 may be one embodiment of acomputer-accessible medium configured to store program instructions anddata as described above for FIGS. 1 through 28 for implementingembodiments of the corresponding methods and apparatus. However, inother embodiments, program instructions and/or data may be received,sent or stored upon different types of computer-accessible media.Generally speaking, a computer-accessible medium may includenon-transitory storage media or memory media such as magnetic or opticalmedia, e.g., disk or DVD/CD coupled to computing device 3000 via I/Ointerface 3030. A non-transitory computer-accessible storage medium mayalso include any volatile or non-volatile media such as RAM (e.g. SDRAM,DDR SDRAM, RDRAM, SRAM, etc.), ROM, etc, that may be included in someembodiments of computing device 3000 as system memory 3020 or anothertype of memory. Further, a computer-accessible medium may includetransmission media or signals such as electrical, electromagnetic, ordigital signals, conveyed via a communication medium such as a networkand/or a wireless link, such as may be implemented via network interface3040. Portions or all of multiple computing devices such as thatillustrated in FIG. 29 may be used to implement the describedfunctionality in various embodiments; for example, software componentsrunning on a variety of different devices and servers may collaborate toprovide the functionality. In some embodiments, portions of thedescribed functionality may be implemented using storage devices,network devices, or special-purpose computer systems, in addition to orinstead of being implemented using general-purpose computer systems. Theterm “computing device”, as used herein, refers to at least all thesetypes of devices, and is not limited to these types of devices.

CONCLUSION

Various embodiments may further include receiving, sending or storinginstructions and/or data implemented in accordance with the foregoingdescription upon a computer-accessible medium. Generally speaking, acomputer-accessible medium may include storage media or memory mediasuch as magnetic or optical media, e.g., disk or DVD/CD-ROM, volatile ornon-volatile media such as RAM (e.g. SDRAM, DDR, RDRAM, SRAM, etc.),ROM, etc, as well as transmission media or signals such as electrical,electromagnetic, or digital signals, conveyed via a communication mediumsuch as network and/or a wireless link.

The various methods as illustrated in the Figures and described hereinrepresent exemplary embodiments of methods. The methods may beimplemented in software, hardware, or a combination thereof. The orderof method may be changed, and various elements may be added, reordered,combined, omitted, modified, etc.

Various modifications and changes may be made as would be obvious to aperson skilled in the art having the benefit of this disclosure. It isintended to embrace all such modifications and changes and, accordingly,the above description to be regarded in an illustrative rather than arestrictive sense.

What is claimed is:
 1. A system, comprising: a plurality of computingdevices configured to implement a plurality of execution platforms of aparticular provider network; and one or more computing devicesconfigured to implement a resource manager; wherein the resource manageris configured to: store a collection of one or more client-providedapplication packages in an application repository, wherein eachapplication package of the one or more application packages comprises arespective executable object of a respective application, and whereineach respective application package has a respective constraint to beused to schedule execution of a respective at least one executableobject of the respective application package; select, based at least inpart on a constraint for a particular application package of thecollection and on a current pricing of execution units of a particularexecution platform, the particular execution platform of the pluralityof execution platforms on which to schedule execution of the at leastone executable object of the particular application package of thecollection; in response to a first price-based interruption event: savea representation of a state of an application of the particularapplication package; and stop execution of the at least one executableobject of the particular application package on the particular executionplatform of the particular provider network; and in response to a secondprice-based interruption event: schedule execution of one or moreexecutable objects of the particular application package on theparticular execution platform or on a different execution platform ofthe plurality of execution platforms of the particular provider network,wherein the execution is based at least in part on the savedrepresentation of the state of the application.
 2. The system as recitedin claim 1, wherein the constraint for the particular applicationpackage comprises an indication of a budgetary constraint from among aplurality of different types of budgetary constraints.
 3. The system asrecited in claim 1, wherein the first price-based interruption eventcomprises: a reception by the resource manager of an additionalapplication package with a different pricing constraint than theconstraint for the particular application package; and wherein thesecond price-based interruption event comprises: a determination by theresource manager that an additional execution platform is available forscheduling application executions, wherein the additional executionplatform has a current pricing of execution units that is different fromthe current pricing of execution units of the particular executionplatform, and wherein the additional execution platform is added to theplurality of execution platforms of the particular provider network. 4.The system as recited in claim 1, wherein the constraint of theparticular application package comprises a bid for at least one of: aCPU-second, a CPU-minute, a CPU-hour, a number of floating-pointoperations (FLOPs), a number of integer operations, or a number of CPUcycles.
 5. The system as recited in claim 1, wherein the constraintcomprises a bid for a completion of execution of the at least oneexecutable object of the particular application package.
 6. The systemas recited in claim 1, wherein the resource manager is further operableto: receive usage data records associated with a client, wherein theusage data records include numbers of resources used, types of resourcesused, hardware stacks used, software stacks used, uptimes, CPUutilizations, I/O rates, device utilizations, network transfer rates,and/or IP addresses; receive pricing information over a period of time;receive an optimization goal; determine, based at least in part on theusage data records, the pricing information, and the optimization goal,a recommendation regarding future instance use of an applicationpackage; and provide the recommendation to the client.
 7. A method,comprising: storing a collection of one or more client-providedapplication packages, wherein each application package of the one ormore application packages comprises a respective executable object of arespective application; receiving a client-provided constraint to beused to schedule execution of at least one executable object of aparticular application package of the collection of one or moreclient-provided application packages; selecting, based at least in parton the constraint, a particular execution platform of a plurality ofexecution platforms on which to schedule execution of the at least oneexecutable object of the particular application package of thecollection, wherein a particular provider network comprises theplurality of execution platforms; in response to a first price-basedinterruption event, stopping execution of the at least one executableobject of the particular application package on the particular executionplatform of the particular provider network; and in response to a secondprice-based interruption event, scheduling execution of one or moreexecutable objects of the particular application package on theparticular execution platform or on a different execution platform ofthe particular provider network.
 8. The method as recited in claim 7,wherein the first price-based interruption event comprises a receptionof an additional application package with a different constraint thanthe constraint of the particular application package.
 9. The method asrecited in claim 7, wherein the first price-based interruption eventcomprises a determination that an additional execution platform isavailable for scheduling application executions, wherein the additionalexecution platform has a current pricing of execution units that isdifferent from a current pricing of execution units of the particularexecution platform, and wherein the additional execution platform isadded to the plurality of execution platforms of the particular providernetwork.
 10. The method as recited in claim 7, wherein the constraintcomprises a bid for a specified number of disk I/O operations.
 11. Themethod as recited in claim 7, wherein the constraint comprises a bid fora completion of execution of the executable object of the particularapplication package.
 12. The method as recited in claim 7, furthercomprising: receiving a quote request for an application package from aclient; and determining, based at least in part on an analysis of theapplication package and on a pricing of execution units of one or moreexecution platforms of the provider network, a quote for completingexecution of the executable object of the application package; andproviding the quote to the client.
 13. The method as recited in claim 7,wherein said scheduling execution in response to the second price-basedinterruption event further comprises: selecting the different executionplatform on which to schedule further execution of the one or moreexecutable objects of the particular application package.
 14. The methodas recited in claim 7, further comprising: assigning a performancecapability rating to one or more execution platforms of the plurality ofexecution platforms; and determining a current pricing of an executionunit on the one or more execution platforms based at least in part onthe performance capability rating of the one or more executionplatforms.
 15. A non-transitory, computer-accessible storage mediumstoring program instructions that when executed on one or moreprocessors: store a collection of one or more client-providedapplication packages, wherein each application package of the one ormore application packages comprises at least one respective executableobject of a respective application and wherein each respectiveapplication package has a respective constraint to be used to scheduleexecution of a respective at least one executable object; select, basedat least in part on a constraint for a particular application package ofthe collection, a particular execution platform of a plurality ofexecution platforms on which to schedule execution of the at least oneexecutable object of the particular application package of thecollection, wherein a particular provider network comprises theplurality of execution platforms; in response to a first price-basedinterruption event, stop execution of the at least one executable objectof the particular application package on the particular executionplatform of the particular provider network; and in response to a secondprice-based interruption event, schedule execution of one or moreexecutable objects of the particular application package on theparticular execution platform or on a different execution platform ofthe particular provider network.
 16. The non-transitory,computer-accessible storage medium as recited in claim 15, wherein thefirst price-based interruption event comprises a reception of anadditional application package with a different constraint than theconstraint for the particular application package.
 17. Thenon-transitory, computer-accessible storage medium as recited in claim15, wherein the first price-based interruption event comprises adetermination that an additional execution platform is available forscheduling application executions, wherein the additional executionplatform has a current pricing of execution units that is different froma current pricing of execution units of the particular executionplatform, and wherein the additional execution platform is added to theplurality of execution platforms of the particular provider network. 18.The non-transitory, computer-accessible storage medium as recited inclaim 15, wherein the constraint of the particular application packagecomprises a bid for a specified number of gigabytes of network datatransfer.
 19. The non-transitory, computer-accessible storage medium asrecited in claim 15, wherein the constraint of the particularapplication package comprises a bid for a completion of execution of theat least one executable object of the particular application package.20. The non-transitory, computer-accessible storage medium as recited inclaim 15, wherein the instructions when executed on the one or moreprocessors: receive a quote request for an application package from aclient; and determine, based at least in part on an analysis of theapplication package and on a pricing of execution units of one or moreexecution platforms of the provider network, a quote for completingexecution of the at least one executable object of the applicationpackage; and provide the quote to the client.
 21. The non-transitory,computer-accessible storage medium as recited in claim 15, wherein toschedule execution in response to the second price-based interruptionevent the instructions when executed on the one or more processors:select the different execution platform on which to schedule furtherexecution of the one or more executable objects of the particularapplication package.
 22. The non-transitory, computer-accessible storagemedium as recited in claim 15, wherein the instructions when executed onthe one or more processors: determine a current pricing of an executionunit of one or more of the plurality of execution platforms based atleast in part on a performance capability rating of the one or moreexecution platforms.
 23. The non-transitory, computer-accessible storagemedium as recited in claim 15, wherein an executable object of a firstapplication package of the one or more application packages comprises afirst thread of execution of a multi-threaded application, wherein anexecutable object of a second application package of the one or moreapplication packages comprises a second thread of execution of themulti-threaded application.
 24. The non-transitory, computer-accessiblestorage medium as recited in claim 15, wherein the instructions whenexecuted on the one or more processors: store output data generated bythe executable during its execution on the particular executionplatform, wherein the output data is stored in a target storagecontainer external to the particular execution platform.
 25. Thenon-transitory, computer-accessible storage medium as recited in claim15, wherein the instructions when executed on the one or moreprocessors: implement a programmatic interface allowing a client toperform at least one of: (a) an upload of at least a portion of anapplication package, (b) a submission of a quote request for theapplication package, (c) a reception of a quote for the applicationpackage, (d) a submission of a request to start execution of anexecutable of the application package, (e) a submission of a request tostop execution of an executable of the application package, (f) asubmission of a request to obtain a current status of an executable ofthe application package, (g) a submission of a bid for the applicationpackage, (h) a submission of a cancelation request for the applicationpackage, (i) a submission of a request for a modification of a bid forthe application package, or (j) a submission of a request for a currentstatus of a bid for the application package.